Internet of things, smart sensors, and pervasive systems: Enabling connected and pervasive healthcare

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Internet of things, smart sensors, and pervasive systems: Enabling connected and pervasive healthcare

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Pijush Kanti Dutta Pramanik*, Bijoy Kumar Upadhyaya†, Saurabh Pal‡, Tanmoy Pal‡ National Institute of Technology, Durgapur, India* Tripura Institute of Technology, Agartala, India† Bengal Institute of Technology, Kolkata, India‡

CHAPTER OUTLINE 1 Introduction ......................................................................................................... 2 2 IoT, Smart Sensors, and Pervasive Computing ........................................................ 3 2.1 IoT ....................................................................................................... 3 2.2 Smart Sensors Augmenting the IoT ......................................................... 4 2.3 Pervasive Systems ................................................................................. 5 2.4 Difference Between Pervasive Systems and IoT ........................................ 6 2.5 IoT and Pervasive Systems: Complementing Each Other ............................ 6 3 Challenges in Traditional Healthcare Systems ........................................................ 8 4 Mobile and Pervasive Healthcare .......................................................................... 9 4.1 Context-Awareness in Healthcare .......................................................... 10 4.2 Connected Healthcare .......................................................................... 11 4.3 Pervasive Healthcare Vs Telemedicine ................................................... 11 5 Role of IoT in Healthcare .................................................................................... 14 5.1 Clinical Care ....................................................................................... 14 5.2 Remote Monitoring .............................................................................. 14 5.3 IoT and Medical Robotics ..................................................................... 14 6 Different Healthcare Sensors ............................................................................... 15 6.1 Basic Health Sensors ........................................................................... 15 6.2 Other Sensors Used in Medical Care Units ............................................. 25 6.3 Different Fitness Devices ...................................................................... 26 7 Benefits of Connected Healthcare ........................................................................ 28 8 Challenges in Connected Healthcare ................................................................... 31

Healthcare Data Analytics and Management. https://doi.org/10.1016/B978-0-12-815368-0.00001-4 # 2019 Elsevier Inc. All rights reserved.

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9 Healthcare Applications of Smart Sensors and IoT ............................................... 34 9.1 Smart Needle ...................................................................................... 36 9.2 iTBra .................................................................................................. 36 9.3 Coronary Artery Disease and IoT ............................................................ 37 9.4 Personalized Medical Care .................................................................... 38 9.5 Patient Monitoring ............................................................................... 38 9.6 Cardiac Rhythm Monitoring .................................................................. 39 9.7 Cardiac Rehabilitation .......................................................................... 39 9.8 Handling COPD Problems ..................................................................... 40 9.9 Smart Contact Lens for Diabetics .......................................................... 40 10 Use Cases ......................................................................................................... 40 10.1 Mississippi Blood Service: Maintaining Logistics Smartly ......................40 10.2 Finding Treatment for COPD ...............................................................41 10.3 Lahey Clinic Medical Center: Tracking Healthcare Equipment in Real-Time .....................................................................................41 10.4 Irin General Hospital: Improving Healthcare Quality ..............................43 10.5 Jefferson University Hospital: Providing Cognitive Environment of Care ..43 11 The IoT Healthcare Market: Present and Future .................................................... 44 12 Conclusion ......................................................................................................... 51 Acknowledgments ................................................................................................... 51 References ............................................................................................................. 51

1 INTRODUCTION Digitization of healthcare data over the past decade has brought revolutionary transformations to the healthcare industry. It has facilitated healthcare data to be more open and easily accessible. Not only have the private players bitten into a share of this apple, but also the government and the public stakeholders of the healthcare industry have progressed towards transparency by making the healthcare data generated and collected from different sources and stored at isolated data islands more usable, searchable, and actionable to all those concerned. Smartphones and tablets, convenient medical apps, wearable devices, and the development of a variety of wireless monitoring services have made healthcare services omnipresent. Medical devices are increasingly being connected to each other [1]. In fact, the trend in the adoption of connected medical devices is set to grow drastically in the coming years. And this rising number of connected medical devices, along with supported software and services, is turning connected healthcare into a proliferating platform for pervasive healthcare. The objective of an ideal healthcare system should be not only to provide effective healthcare services but also to support patients with quality of life by ensuring optimal functioning of overall health monitoring. This goal has led to the concept of a pervasive healthcare system that is able to monitor health status, provide medical facilities, and ensure sound health regardless of the location of the beneficiary. The traditional healthcare systems are highly concentrated in hospitals and clinics [2], but most people prefer to receive health services at their own residences as much

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as possible. Even if they are required to use institutional medical facilities, they wish to minimize the time spent there. Typically, the direct clinical healthcare received by humans, on average, is negligible in comparison to the overall healthcare needed during a lifetime. Smart sensors [3], Internet of Things (IoT) [4, 5], and wearables [6, 7] have augmented the healthcare system, enabling remote monitoring and supporting the medical condition of patients in and out of clinics [8]. For instance, the blood glucose monitor may send a reminder to a diabetic patient to take insulin. If the patient is a pediatric diabetic, the system might suggest that parents recheck the diet plan if the sugar level continuously approaches higher levels. Similarly, a wearable sensor allows an orthopedic physician to monitor a patient as to whether the patient is doing prescribed exercises properly and regularly. Smart sensors and the IoT will allow clinicians to have passable and unified access to the details of their patients, including food habits and lifestyles. This means that collecting only the clinical data is insufficient. To get the real picture of the health status of an individual or the mass public, peoples’ health data need to be collected and analyzed on a regular basis, even if they are not a clinical patient [9]. Using current technology, patients can continuously be monitored even they are not under clinical care. The pervasive health applications have significantly increased health data liquidity, which has elevated the healthcare service industry as never before. Pervasive healthcare [10, 11] not only will allow healthcare service providers to monitor and manage patients remotely, but the patients also will be able to track their own medical records and status, perform basic analytics, and seek consultancy from doctors, pharmacists, and hospitals by referring to those documents. Easy-to-use app interfaces connected to the medical devices and databases have empowered users with easy and ubiquitous access to medical data through mobile devices. The rest of this chapter is organized as follows. Section 2 provides a brief overview of IoT and pervasive computing, pervasive systems, and their interrelationships. Section 3 highlights the challenges in traditional healthcare systems. Section 4 covers the basics of mobile and pervasive healthcare, including context-aware and connected healthcare, while distinguishing it from telemedicine. Section 5 emphasizes the role of IoT in healthcare. Various smart sensors related to healthcare, fitness and medical care units are discussed in Section 6. Section 7 covers the benefits of connected healthcare, while Section 8 points out the challenges in pervasive healthcare. Several real-life applications of IoT and smart sensors are presented in Section 9, showing the effectiveness of pervasive healthcare. Some use cases are discussed in Section 10. Section 11 presents an assessment of the current and future IoT healthcare market. And finally, Section 12 concludes the chapter.

2 IoT, SMART SENSORS, AND PERVASIVE COMPUTING 2.1 IOT IoT extends the Internet from connected computers to connected objects. The objects or “things” can be anything, provided they are connected to the Internet directly or indirectly [12]. The purpose of this huge-scale connectivity is to enable access to

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information pervasively and ubiquitously. This means information on any object can be accessed from anywhere. All the objects in the IoT have unique IDs making them identifiable on the Internet. In the Service Oriented Architecture (SOA) perspective, the objects have a digital representation on the Web for easy and flexible accessing through normal web portals. The basic components of IoT are [13]: • • • •

Sensors (e.g., temperature, light, motion, etc.) or actuators (e.g., displays, sound, motors, etc.) Computing resources (for processing sensor data) The communication medium (Bluetooth, ZigBee, RFID, etc., for short range and the Internet for long range) Application interface (for accessing IoT services)

In IoT, the “things” are typically embedded with some sort of sensors that sense the surrounding data and send them to a centralized housing, which is generally a private or public cloud. The sensed data are processed and analyzed here and, depending on the outcome, some events are triggered and notified to the subscribed application [14]. This whole concept allows remote monitoring of any object that is connectable. In IoT, the ability to identify an object globally, by other IoT devices, not only increases the utility of that object but also gives the ability to interact with other devices and communicate with the surrounding environment, making the things smarter and offering an overall intelligent environment surrounding that object.

2.2 SMART SENSORS AUGMENTING THE IOT The driving philosophy of IoT is to gain knowledge about an environment, state of things, user’s situation, and activities. This knowledge is made possible by sensors embedded in the things. The sensors, which act as the nervous system of IoT, consistently sense and capture the necessary data from the device itself, the environment, and users. In general, IoT devices are not intelligent but with the addition of smart sensors, these devices are transformed into smarter ones. The data thus gathered by sensors can be analyzed to find hidden patterns and to predict user need, device operability, etc. Learning from the procured data is what actually transforms IoT into an intelligent system. Based on the learning, appropriate services can be provided while peer devices interact or willing to interact. The application of sensors in devices has definitely made IoT an intelligent system. But the application of sensors has its own intrinsic issues related to sensor connectivity, integration and control, and data processing. Some of the issues associated with the usual sensors embedded in a device are: •

Sensors attached to devices produce an enormous amount of data to be streamed over the Internet. The sheer volume of data produced by sensors puts a huge burden on a network; due to network latency, data are often not processed synchronously or are lost. This creates a major setback for any real-time

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•

•

• •

applications that demand instant feedback, as late arrival of processed feed due to network latency causes a delay in real-time action. The other associated issue is the fact that sensors produce an enormous amount of noisy raw data and processing these data and filtering the noise is a CPUintensive job. Sensors produce data in a raw format. From the data integration and usability perspective, this raw data may not be acceptable to other heterogeneous systems. It is often necessary to abstract the data by extracting the needed information and representing it in a form acceptable to other heterogeneous systems. Sensors are prone to fault, producing erroneous or no data, and this raises a need for run-time diagnostics to determine the cause and magnitude of errors. Further, the usual sensors are separate entities that need to be connected separately to the interfacing circuit of the device. This causes difficulties related to embedding sensors into the device as well as their maintenance.

These issues have existed for some time in the industrial and research sectors, and to address them, sensors have improved over the years. In particular, they have evolved over several generations to become smart sensors, capable of performing a logic function, two-way communication, and decision making. A smart sensor consists of an actuator interfacing circuit, a sensing element, and a signal processing unit consisting of processor, memory, and software [15, 16]. A smart sensor can also be referred to as a basic sensing mechanism with embedded intelligence [17]. It can detect signals from multiple sensing elements, perform signal processing, data validation, interpretation and logging. Advances in sensing technologies and intelligent data processing have brought automation to the healthcare system. Smart sensors have truly taken IoT a step further by making it intelligent. Now instead of sensing and transmitting all the raw data, smart sensors can pick and transmit only the relevant data for further processing and storage, and hence reduce the network load. The embedded software program helps by filtering the noise from the raw data and then transforming it into a form that is portable and comprehensible to other systems. Further, self-calibration ability helps in self-diagnostics and making adjustments for error-free data sensing. In real-time systems, the embedded software in the smart sensor allows for self-decisions and thereby the actuator circuit can be instructed to perform necessary actions in real time. The use of smart sensors in IoT has transformed it into an accurate, fast, reliable and intelligent system. Smart sensor in IoT are often fused together, enabling context awareness and giving a holistic picture of the entire scene. Services can be invoked based on the context of what a user is doing, what action a machine is performing, and the state of the infrastructure and environment, or a combination of all [18].

2.3 PERVASIVE SYSTEMS The origin of the term pervasive is the Latin word pervadere, which means to spread or to go through. The word pervasive has been derived by blending the past participle

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stem of pervadere—or pervas—and the “ive” from English. The Cambridge Dictionary defines pervasive as “present or noticeable in every part of a thing or place.” Hence, a pervasive system refers to a distributed computing system that comprises computationally enabled devices and information systems that provide computation and, consequently, information anywhere and anytime. Pervasive computing enables small, low-powered, and embedded devices to compute the sensed or incoming data and disseminate the processed information to the desired sink wherever it is, with the help of ubiquitous communication networks. The idea of pervasive computing is to equip commonly used everyday objects with some sort of computing facility. Empowered by this embedded computing, these objects become digitally functional. The objects may also be connected to the network for remote accessing, thus adding more value to the system. In contrast to desktop computing, pervasive computing is done on any device, at any time and in any place, regardless of the data format. When integrated, the devices are capable of handing off tasks among each other, if required, for better task flow. The main objective of pervasive computing is to make the objects used in daily life interact with a human. Empowered by embedded computing abilities, these objects become more intelligent. The richer interaction between humans and intelligent physical objects creates ambient intelligence and thus improves the living experience of human beings.

2.4 DIFFERENCE BETWEEN PERVASIVE SYSTEMS AND IOT Pervasive computing and IoT are often confused, as if they were synonyms. The reason behind this confusion is that both computing paradigms have many similarities. For example, both try to infuse “life” into every physical object, making the objects “intelligent.” Devices in both systems are generally small—at the micro or nano level. Both aim to minimize human effort in everyday jobs. But despite the similar and overlapping properties, these terms differ in some parameters. Table 1 summarizes the differences between the two.

2.5 IOT AND PERVASIVE SYSTEMS: COMPLEMENTING EACH OTHER Even with the differences discussed here, pervasive computing and IoT seem to be inseparable. They need each other to realize their respective goals. Need for pervasive computing in IoT: Usually the IoT devices have limited or no computing capacity. To process the sensed data, they must depend on some local or remote processing units. The omnipresence of computationally enabled pervasive devices can support in this aspect. Need for IoT in pervasive systems: Due to the inherent ubiquity, IoT has become one of the key factors in realizing the full value of pervasive systems. In pervasive computing, the computing is dispersed throughout common objects used in daily life. IoT can extend this vision by knitting these disconnected and distributed objects together by connecting them to the Internet, making them not only

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Table 1 Difference between pervasive systems and IoT Era of origin Defining point Vision

Purpose

Goal

Focus Designing emphasis

Interaction with neighbors

Devices’ computing capability

Internet connection requirement

Pervasive system

IoT

The early 1990s All the physical objects should have computation capability The vision of pervasive computing was to make computing available anytime and anywhere To make the living experience of a human being much richer and more interesting by creating ambience intelligence among surrounding objects Provide a suitable platform for infusing intelligence into everyday objects by empowering them with computing facility and enabling users to interact with these objects Human-to-machine interaction The core effort of designing pervasive systems is to make the devices self-sufficient in terms of computing that is required for ambient intelligence The pervasive computing devices may be isolated or loosely coupled with other devices in the neighborhood. Hence, the degree of interaction with the neighbors is less The devices in a pervasive system necessarily have some computing power

The late 1990s All the physical objects should be connected The vision of IoT was to extend the principles of the Internet beyond the computers to physical things To automate many of the simple but essential daily chores without human intervention, thus relieving human beings to a significant extent Connecting all the physical objects, enabling them to interact among themselves, which will help in global automation

Philosophically, pervasive computing does not necessarily say that the objects should be connected to the Internet. It just says that every object should be able to compute. But without a global connection, the full benefits of pervasive computing cannot be achieved

Machine-to-machine interaction IoT is more about virtual representations of automatically identifiable objects

IoT devices are tightly coupled with other devices in the neighborhood. In most of the use cases, a number of devices work as a team for a particular purpose

It may not always be true for IoT devices. Many of the IoT devices are used only for sensing, with the computing job being offloaded to some other capable device The goal of the IoT vision is to access and control things remotely, for which the devices need to be connected to the Internet directly or indirectly

Continued

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Table 1 Difference between pervasive systems and IoT—cont’d Pervasive system

IoT

Network standards

For communication, pervasive systems follow the traditional communication standards, such as IP

Network permanency

If the devices are connected, a major possibility is that they are connected through an ad-hoc connection rather than a permanent connection All the computing points are basically vulnerable. Hence, the greater the span of pervasive systems, the more security concerns

For IoT, besides IP, some other specific standards are used, such as 6LoWPAN (IPv6 Low Power Wireless Personal Area Network), RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks), etc. As the IoT devices generate data continually and most often the data must be transported immediately, a permanent connection is required The widespread network with inclusive connectivity increases security vulnerability. The threat is greater than with pervasive systems

Security threat

computationally enabled but also globally connected. IoT makes pervasive systems more context-aware by providing a considerable amount of contextual information. This helps in improving the overall activity of the user. If the pervasive system is considered as the objective, then the IoT is one of the enablers to achieve that. With the help of IoT and its widespread adoption, pervasive computing can do wonders. The merger of IoT and pervasive computing, along with AI, gives us the foundation of cognitive IoT, which is going to change our lives in a major way [13]. Actually, both these concepts are being enhanced and fused and, subsequently, the differences between them have become blurred. That is why today these terms are often used interchangeably. In fact, the purely academic definition of these terms has insignificant value within the context of the rising popularity of their applications among the common people.

3 CHALLENGES IN TRADITIONAL HEALTHCARE SYSTEMS In spite of the significant advances in the medical sector, the potential benefits are not being passed on to the patients who need them, due to today’s inefficiently implemented healthcare systems. The existing healthcare systems face several challenges [19]: •

Thanks to the advances in medical science, related technologies, and healthcare delivery, the average lifespan of humans has increased by a significant margin. Hence the size of the senior population is growing considerably. Along with this aging population, the number of patients suffering from chronic conditions also

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• • •

•

• •

increases. These chronic diseases require continuous observation and treatment, which places an additional burden on the existing inadequate healthcare infrastructure. Both public and private hospitals and clinics are experiencing shortages of qualified, experienced, and skilled medical professionals and experts. The accessing and delivering of healthcare services are becoming more costly as time goes on. Modern erratic and unhealthy lifestyles have caused different unforeseen disease patterns to emerge. Population health trends are shifting towards a challenging clinical disarray. Due to discrete and case-by-case diagnosis and treatments, traditional healthcare systems involve a high rate of hospital readmissions. This leads to further stress and strain along with repeated and intricate follow-up care. Lack of on-site medical facilities, experts, and global healthcare information systems increases the average length of stay in the hospital. The high rates and longer durations of hospitalization definitely make bigger holes in patients’ wallets, which is a real concern, especially for the lower socioeconomic groups.

The root cause of the incapability of our traditional healthcare systems to overcome these challenges is the discrete and isolated nature of the existing medical care facilities. The present healthcare system can hardly be called a system [20]. The hospitals and healthcare facility centers are working in silos. The infrastructures are built as isolated set-ups that do not interact among themselves. Also, a significant number of physicians practice solo, not connected to any healthcare system. They operate without any formal communications and collaborations. Although some systems are implemented by large companies with a long chain of hospitals across cities and even countries, they are not well designed. The lack of an integrated system directly affects the patient care services. The most critical, as discussed previously, is the coordination of continued care across different hospitals and for different diseases. Lack of coordination results in redundant and overlapping processes, resulting in delays in diagnosis and treatment, patient suffering, and increased medical bills [20]. The same applies when the patient is shifted to home for rehabilitation. Fragmented and ill-coordinated procedures affect the after-treatment care. To properly utilize the medical sector advances, we need an all-inclusive healthcare system that will integrate patients, different healthcare service providers, and other stakeholders.

4 MOBILE AND PERVASIVE HEALTHCARE The incorporation of IoT into healthcare services reasonably allows pervasiveness. The added pervasive features like mobility, adaptability, and context awareness provide the right information to the right person at the right place and time, adding great

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value to the modern health system. Pervasive healthcare envisions transforming the healthcare service focus from illness to wellbeing and staying healthy. For example, technology applications such as mobile devices, wireless links, and mobility enable trauma and emergency service personnel to send a patient’s medical details while in transit to the hospital. When a patient is in the close proximity to the doctor, the patient’s medical, health, and insurance data can be transferred from the patient’s mobile device to the physician, assuring that issues like allergies, blood pressure, glucose level, and other problems can be preassessed as a precautionary measure before starting the treatment. Similarly, doctors with smart devices have access to the patient’s vital status whether during an office visit or remotely from any other location. Besides the benefits to diagnosing, the mobility and pervasiveness of IoT devices allow monitoring of a patient’s vital statistics no matter their physical location. Wearables and health monitoring sensors continuously collect a patient’s physiology information, such as body temperature, heart rate, blood pressure, oxygen level, etc. A pervasive information system allows doctors and patients’ families to remotely access these health records. A close and precise observation can be made from anywhere for critical patients, whether they stay at home or in a hospital. Location-based services using GPS or RFID would enable tracking and supervision of patients suffering from mental illness, elderly persons, and disabled persons. A smart mobile application could remind the patient about routine check-ups and medication based on the patient’s current health context [21]. A wide range of mobile and pervasive healthcare applications like mobile telemedicine, personalized monitoring and assessment, location-based medical services, emergency response and management, and other context-based services are improving health services and patient satisfaction [21]. One of the significant characteristics of pervasive systems is adaptability. A patient’s contextual information like medical state and other situational information like the patient’s background and habits, environment, location, and social relationships are being used in making diagnostic decisions. These personalized diagnostics ensure treatment adapted to the patient, leading to more precise treatment [21]. Pervasive technology focuses on managing healthcare by looking forward, not only to the cure, but also to promoting health and wellbeing throughout a lifetime, as prevention is always better than cure. Pervasive technology can continually monitor and sense one’s health status before any medical event actually happens. Instead of monitoring for one medical parameter like ECG, the technology can look for multiple parameters that influence one’s health prospects. These data coming from various sensors are fused together to predict the present state and future medical complication [22]. An intelligent data processing platform and the natural interacting software can make decision-making more intelligent and context based.

4.1 CONTEXT-AWARENESS IN HEALTHCARE In evidence-based medical treatment, diagnosis is performed upon seeing the patient’s signs and symptoms. But for chronic and critical illness with a prolonged ailment history, these types of treatments are often not effective. For effective

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treatment, it is necessary that the patients be monitored continually. In treating a medical event, it is important to understand patient context, which is the situational information that uniquely describes the patient’s medical condition. Patient context includes patient profile (e.g., name, age, weight, gender, and eating and sleeping habits), behavior and activity information, medical history, current medical condition, when medication is taken, etc. Analysis of patient context is very applicable to prescriptive decisions. Context-aware treatment would lead to personalized treatments that definitely prove effective for the particular patient. Sensor-based IoT devices provide an opportunity for context-aware health services. Sensor-based medical devices constantly sense the patient’s vital statistics such as glucose level, blood pressure, the oxygen level in blood, breathing, heart rate, brain activity, and chemical balance of the blood. These sensor devices, when connected to the internet, can record patients’ medical data over time. The patient contextual information, including present vital statistics and previous medical data, on analysis would enable the physician to access the complete medical situation of the patient, thus helping in proper diagnosis.

4.2 CONNECTED HEALTHCARE The other opportunity sensor-based IoT provides is connected healthcare. Sensors monitoring a patient connected over the Internet gather the patient’s critical data and transfer them to be stored. The data recorded can be shared with the physician to be analyzed further. This helps patients to get treatment from suitable doctors, clinics or hospitals across geographical locations, without worrying about carrying medical records or repetitive tests and diagnostic procedures. The connected device allows the physician to monitor a patient’s vitals remotely, literally from any location having an internet connection. The data exchanged between connected devices includes vital medical data like textual data, mostly numeric values, images, and video data as sonography, endoscopy, etc. For an automated remote monitoring system, patients are automatically monitored for any health complication. Any deviations in the data sensed are automatically analyzed, and the doctor and emergency services are notified. Further, the connected medical devices and medical services increase patient engagement. The patient is more informed and connected to physicians, medical staff, hospitals, clinics, and the insurance company. Though the potential of the connected devices and their pervasive applications is great, still deeper exploration is needed to deliver the best practical applications.

4.3 PERVASIVE HEALTHCARE VS TELEMEDICINE Since both involve remote operation, pervasive healthcare and telemedicine are often confused, though they are quite different approaches to healthcare. Telemedicine emphasizes clinical healthcare services such as diagnosis and recommendations from a distance using telecommunication as a medium of interaction [23].

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Much of the interaction between doctor and patient happens using telephone or Internet while consulting doctors are geographically a distance apart from the patient. In contrast, pervasive healthcare is an automated approach for remote health monitoring and prediction. The following brief description of the what and how of these techniques elaborates on the need for each. Telemedicine: Telemedicine is an approach to practicing medicine and clinical services from a distance, using telecommunication. It is used to overcome distance barriers and doctor shortages in rural or geographically remote areas. Telemedicine can be categorized into three types [23]: (i) Store-and-Forward (ii) Remote Monitoring (iii) Real-time Interaction In store-and-forward, the medical data of patients are sent to doctors for assessment. This is an asynchronous process and does not need both parties to be present at the same time; doctors at their convenience can assess the reports. Remote monitoring involves doctors or medical staff remotely monitoring a patient’s vital statistics in real time. Sessions are created where a patient at their own convenience at home or a nearby medical facility can interact with doctors using a telecommunication link [23, 24]. In general, practicing telemedicine over a distance consists of a doctor or group of doctors at one end with medical staff administering the patient or the patient alone at the other end, with the two ends communicating through the link. Doctors at a distance from the patient handle diagnosis, decision making, and recommendations using the link. Technologies like mobile communication, video conferencing, fax, scanners, and the Internet are widely used to communicate and exchange documents. The doctors assess a patient based on the video, X-ray and sonography images; infection photographs; and documents like prescriptions, pathological reports, ECG reports, etc., to make recommendations. Video conferencing and audio conversations are carried out for communication between doctors and patients. Telemedicine is a cost-effective way of bridging the gap between doctor and patient. Using the telecommunication advantages discussed, high-quality medical consultation can be provided to patients in almost any corner of the earth. This would help in increasing the availability of doctors to patients regardless of distance, caste, creed, and economic status [25]. Pervasive healthcare: In contrast to telemedicine, IoT is an approach for automated health monitoring. Precision in sensing and real-time analysis has given rise to applications like remote health monitoring and care of elderly or disabled persons. An IoT healthcare system is an amalgamation of different technologies, such as the Internet, Wi-Fi networks, sensors and embedded devices, and ubiquitous computing [26]. The objective of biosensors is physiological data collection, while IoT enables these devices (sensors) to interact with a data-processing platform over the Internet. Biosensors, embedded inside or attached outside to (the body of ) a patient, sense the different vital parameters. The physiological data are collected and subsequently transmitted to a local processing station using wireless links like Wi-Fi or Bluetooth.

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The data collected at the local subsystem can be processed either locally or in the remote system. The data sent to remote systems are collected, stored, and analyzed for any anomalies. For any anomaly found in the data pattern, an alert is raised for urgent medical services. Often, for a quicker and more timely response, data are processed at a local subsystem, with the crucial/significant data being sent to the remote system for further analysis [27]. IoT devices capture health data over a continuum; the data recorded over the past can be analyzed for monitoring and predicting future health problems and patient progress in health fitness. Thus, IoT gives better opportunities to monitor and keep track of the patient remotely, with vital parameters such as temperature, heart rate readings, blood pressure, blood glucose, brainwaves, and oxygen level in the blood being captured through IoT devices and analyzed later on. Since health check-ups can be done at any convenient place, such as the patient’s home, routine visits to hospitals and other health service centers can be avoided. The advances in biosensors and the increasing popularity of wearable devices and health monitoring systems have led to numerous medical health applications [27]. Common sensors that have been widely used for monitoring patients are: • • • •

Inertial motion sensor (for monitoring human body posture) Bioelectrical sensors (ECG, EMG, EEG) Electrochemical sensors (for measuring glucose level, CO2 and oxygen level in blood, etc.) Temperature sensors

For the elderly and those suffering from chronic illness, wearable sensor devices enable constant monitoring of a person’s health. If any anomaly is found in the vital readings, the issues can be reported immediately. These wearable devices connect to the internet, collect the patients’ health data at a remote location, and send it to the hospital and to physicians, allowing for real-time monitoring of these patients. A fitness band wirelessly connected to tablets or mobile devices reports a person’s vital signs. Besides monitoring the health status, these devices also remind the patient to take medications, do exercises, and check blood pressure and cardio at a scheduled time. Different instruments like glucometers, cardio monitors, and blood pressure monitoring devices connected to IoT have been preferred by patients at home and also in hospitals [28]. The purpose of both the IoT and telemedicine is the betterment of peoples’ health, but in a different manner. Telemedicine incorporates doctors taking the lead role in assessment, decision-making, and recommendations, while IoT in healthcare tries to make monitoring, assessment, and predicting patient health more automated. The perspective of IoT in healthcare is improving a person’s health by monitoring and predicting health issues over a period and making health services available 24
7, while telemedicine is a process whereby physicians in a short session assess a patient’s current medical condition and make recommendations based on the signs/ symptoms. IoT in healthcare is a technologically intensive development. Automatic prediction and diagnosis need huge data processing and cognition; despite many pioneering advances, IoT still lacks the cognition for predicting and diagnosing a

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patient. The lack of true machine intelligence means that human expertise and cognition for patient treatment must still be sought. In contrast, the telemedicine process is a human/expert intensive process; doctors with their expertise make the diagnosis. It will be a long time before IoT will fully automate healthcare services (if ever); perhaps the real-time characteristics of IoT will be complementary to telemedicine. Physicians and other medical staff could have a real-time picture of a patient’s health status, and the past data patterns would enable them to analyze the patient issues more thoroughly and provide a correct diagnosis.

5 ROLE OF IoT IN HEALTHCARE 5.1 CLINICAL CARE Diagnosing a patient often requires various tests of blood, breathing, urine, cardiac status, etc. These tests, when carried out in a laboratory, take time to conclusively find the results. In an emergency, prescribing suitable medicine or treatment requires knowing the necessary vital statistics of a patient like glucose level, blood pressure, cardiac condition, etc. Sensor and sensor-based IoT for medical aids in this direction can provide a quick and pervasive way to test a patient’s vital statistics. In an emergency situation, such a device quickly assesses the patient anywhere and any time, without the patient waiting a long time for test results. The fast results can help doctors to correctly diagnose the patient, possibly saving a life. Further, using noninvasive IoT devices to monitor patients in hospitals, clinics, or at home can gather needed information about a patient over a long time, which can then be stored and analyzed. The analyzed data provides information over a continuum, which helps in yielding better clinical care at lower cost.

5.2 REMOTE MONITORING Sensor and sensor-based IoT devices for medical aid provide a unique opportunity for patient remote monitoring. Whether the patient is in hospital, at home or staying anywhere else, the use of IoT enabled medical aid and services would allow doctors to have patient information at their fingertips. A different electronic sensor connected to the patient could monitor vital statistics like chemical imbalances in the body, glucose level, nerve and brain activity, blood pressure, cardiac status, and further psychological and behavioral conditions. IoT devices connected wirelessly ensure that vital statistics data are available to doctors around the clock and from any location. Applying data analysis over the collected data would help physicians to make correct recommendations remotely.

5.3 IOT AND MEDICAL ROBOTICS Robots are machines programmed to perform tasks. Robots are quite useful in performing complex jobs that are time-consuming, laborious, and demand precision. Robotics have been used for decades in industrial applications, but in recent years

6 Different healthcare sensors

their application in the medical and healthcare sector has grown. Robots perform such integrated services as patient care and rehabilitation. The application of robotics has significantly improved areas such as patient monitoring, surgery, smart medical capsules, devices for leg and arm amputees, muscle disorders, and patients who have a cognitive or mental disability. Robots act in the real physical world, but prior to acting it is important to comprehend the context. IoT acting as the sensory level provides input to robots. The sensors and IoT devices detect the patient’s situational information and make meaningful contextual sense of the information by gathering real-world inputs. The data are processed intelligently to take appropriate real-world action. IoT sensors, besides informing robots, also send the data for storage and further analyses. The data analysis then helps in gaining better insight into the situation and further development of the robots. For a prosthetic robotic arm or leg, the sensors attached to the amputated region sense muscle pressure and the nerve system to identify the patient’s intention. Similarly, a camera providing visual sensory input analyzes the operating area and informs the robot to perform the necessary surgery. Similarly, sensors and IoT devices that continually monitor patients can inform a robot, based on patient situations or context, to attend the patient for medication or help the patient in rising from the bed or walking, etc. Medical robots are very useful, but to act appropriately they need IoT devices as sensory input to assess the situation [29].

6 DIFFERENT HEALTHCARE SENSORS 6.1 BASIC HEALTH SENSORS The health sensors are the most important components of the pervasive healthcare system. They are used to sense different health conditions and to keep track of health information. Since health sensors are implanted on or in the body to read the biological data, they are also referred to as biosensors. Different types of biosensors are deployed to measure various types of biological signals such as blood pressure, body temperature, oxygen saturation, heart rate, etc. in the human body under the aegis of a pervasive healthcare environment, using IoT. The working principle of these devices may vary depending on their applications. For example, the oxygen saturation biosensor, also known as a pulse oximeter, employs an optical sensing mechanism to determine light absorption at two different wavelengths. Fine wires blended in the jacket are used to intercept the electrical signals corresponding to the body temperature of a patient. However, in a broader perspective, these sensors may make use of some common characteristics in terms of their construction and functionality, as shown in Fig. 1. In general, the biosensors may be composed of the following four main parts [30, 31]: • • • •

Bioreceptor Transducer Signal processor Output/communication system

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Bioreceptor

Transducer

Signal processor

FIG. 1 Schematic diagram of biosensors.

The bioreceptor senses a biological parameter in a human body. Bioreceptors are also referred to as recognition elements and may be of various types, such as antigen, antibody, enzyme, protein, etc. The parameter under consideration is translated into the equivalent electrical signal by the transducer block. A biosensor may use electromechanical, optical, mass change or calorimetric, etc., types of transducers, depending on the nature of the input. The signal so obtained may be contaminated with noise and need filtering. In addition, the strength of the signal needs to be enhanced so that it can be sent for display or transmission for storage and analysis purposes. The signal processing block performs the noise removal and amplification operation. Elimination of noise is usually done with the help of digital finite impulse response (FIR) filters. Operational amplifiers (op-amps) are the ideal choice to raise the strength of a weak signal. The local display block is optional. In a pervasive healthcare system with IoT, the biological parameter so obtained is transmitted to the server located in the healthcare center using various wireless protocols such as Wi-Fi, Bluetooth, ZigBee, and so forth. In this section, different health sensors supporting pervasive healthcare systems are discussed. Table 2 summarizes these devices, mentioning the associated challenges.

6.1.1 Blood pressure sensor Blood pressure measurement aims at determining pressure flowing through the blood vessels against the artery walls. The blood pressure is said to be normal if the flow of blood in the artery is normal. Due to some reason, if blood flow is restricted, then the blood pressure goes high. Increased blood pressure may cause severe medical problems [39]. The device used to measure blood pressure is called a sphygmomanometer. The blood pressure measurement process identifies two pressures inside the blood vessels: one, when the heart beats, is called the systolic pressure, and the other, when the heart is at rest between two heartbeats, is referred to as diastolic pressure. There are several conventional blood pressure measurement methods available today. A mercury sphygmomanometer is considered to be the “gold standard,” which consists of a straight glass tube in assembly with a reservoir containing mercury. An aneroid sphygmomanometer is another type that works on a similar principle to that of the mercury sphygmomanometer, but instead of mercury it uses a mechanical dial to display the blood pressure. The digital manometer is based on the oscillometric

Table 2 Different healthcare sensors supporting a pervasive healthcare system and their challenges Application area Health monitoring

Device Blood pressure sensor Body temperature sensor ECG sensor

EEG sensor

Acceleration sensor Pulse oximeter Heart rate monitor Cardiac rhythm monitor Pill camera

Sensor technology/ sensing mechanism

General purpose/ focus

Communication protocols used

Pulse transit time (PTT) [32]/pulse wave transit time (PWTT) [33] Thermistor/ thermoelectric/optical based Capacitively coupled [35]/insulated electrode [32] ECG Noncontact biopotential electrodes [36]

Detection of hypertension

Wi-Fi, Bluetooth, ZigBee

Detection of fever/ circulatory shock [34]

Bluetooth

Piezoresistive/ piezoelectric/differential capacitance types Infrared light based Infrared light based Capacitive electrode [37] Capsule camera

Identifies cardiac abnormalities

Bluetooth, ZigBee

Determines various electrical activity in the brain Monitoring human physical activity

Bluetooth

Determines oxygen level in blood Determines cardiovascular fitness Detection of irregular heart functioning

Bluetooth, ZigBee Bluetooth, ZigBee Bluetooth, ZigBee

Identification of various gastrointestinal tract disorder

ZigBee, Ant, Ultra-Wide Band (UWB), Bluetooth

Bluetooth, ZigBee

Communication challenges

• Signal

• • • •

• •

attenuation by body’s line of sight absorption Low power communication Radio Frequency Interference from multiple sources Handling of huge computational loads Availability of ubiquitous mobile networking Identification of each patient uniquely Prioritization of vital signals over others

Data processing challenges

• Confidentiality • • • •

•

of patients’ information Secure access control Privacy of patients Secure wireless networking Protection against malicious modification Distributed data access security

Continued

Table 2 Different healthcare sensors supporting a pervasive healthcare system and their challenges—cont’d Application area Medical care unit

Fitness

Device Room temperature sensor Barometric pressure sensor Light sensor

Motion and activity sensor Wristband

Sensor technology/ sensing mechanism

General purpose/ focus

Communication protocols used

Communication challenges

Data processing challenges

Thermistor/resistive temperature detector (RTD) Capacitive sensor/ microelectromechanical systems (MEMS) Light dependent resistor (LDR)/photo diode/ photo transistor MEMS sensor

Monitoring and control of room temperature

Wi-Fi

Monitoring of room pressure and proper airflow Illumination control

Wi-Fi

Wireless networking with reliability, dependability, suitability for healthcare providing infrastructure

Relatively lower level of data security requirement

Detection of mobility

Bluetooth

Counting of heart rate, steps, calories consumed, etc. Monitoring of pace, heart rate, cadence, and power, etc. during physical activities like swimming, cycling, etc. Keep track of gait and physical fitness

Bluetooth

• Low power

• Confidentiality

Bluetooth

communication • Availability of ubiquitous mobile networking

of user information • Secure access control • Privacy of user

Optical sensor

Eye gear

Digital sensor technology

Smart shoe

Ground contact Force (GCF) sensor [38]

Wi-Fi

Bluetooth

6 Different healthcare sensors

principle of measuring blood pressure and uses an electronic pressure sensor for measuring the blood pressure; the readings are given out digitally on a display. The various methods described so far use a cuff, which is not suitable for continuous monitoring in the pervasive environment, especially while sleeping. One of the viable methods for ambulatory blood pressure monitoring in the pervasive scenario is pulse transit time (PTT) [32] or pulse wave transit time (PWTT) [33]. PTT refers to the time delay between two arterial sites. PTT can be estimated from the time gap between the proximal and distal arterial waveforms. Blood pressure is inversely related to the PTT. Finally, the PTT values in a millisecond are calibrated into blood pressure in millimeters of mercury. This method of blood pressure measurement is cuffless and can be interfaced with a smart hub, such as a smartphone, to support a pervasive healthcare system.

6.1.2 Body temperature sensor Body temperature is one of the important signs to provide insight into the physiological state of a person [40]. The normal core body temperature is approximately 37°C. An abnormal body temperature may be considered as an important indicator that the person is suffering from an infection, fever, or low blood flow due to circulatory shock [41]. The body temperature of a healthy person may also vary marginally depending on the time of measurement during the day and the location of the measurement on the body. Therefore, while measuring the temperature, care must be taken to calibrate the temperature readings appropriately. In the pervasive healthcare environment, wearable temperature sensors are often used and are placed on the wrist, the arm, or the chest. The temperature of these body parts is lower by approximately 5°C than the body-core temperature. In wearable and other noninvasive technology, thermistor-based sensors are preferred over thermoelectric or optical-based sensors for body temperature measurement [40] due to their improved sensitivity and accuracy. The resistance of a thermistor varies with respect to change in temperature. In one class of thermistor, called positive temperature coefficient (PTC) type, the resistance increases with increase in temperature. In the other category, the resistance decreases with a decrease in temperature and these are referred to as a negative temperature coefficient (NTC) type thermistor. Conductive textile wires are used as the NTC type of sensor in the wearable smart jacket for neonatal patients [42]. In addition, nickel and tungsten wires are popularly used as fabric sensors due to their high reference resistance, sensitivity, and availability for such wearable applications. Temperature sensors based on integrated circuits (ICs) like the LM35 may also be directly placed on the skin of a patient requiring continuous temperature monitoring.

6.1.3 ECG sensor Electrocardiography (ECG) is one of the oldest and simplest tests used to determine vital information about the cardiovascular system of a patient [35]. An ECG shows electrical activity of the heart muscles in response to electrical depolarization, which is traced on graph paper. An ECG can be performed using various techniques.

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One conventional method, namely wet ECG, in which 12 or 15 Ag-AgCl electrodes are fitted to the chest, arms, hands, and legs, uses a special type of conductive gel that works as a conducting medium for electrical signals from the body to the electrodes. Wet ECG suffers from drawbacks with long-term use, such as patient allergies due to contact with metal electrodes and the gel, or surface degradation of electrodes leading to deterioration of signal quality. In the past few decades, there has been a sharp increase in coronary diseases, especially for the elderly. In the case of high-risk patients, continuous monitoring of the ECG signal may be very helpful in immediately detecting pathological signatures and arrhythmias [35]. In such situations, deviations from normal ECG readings can be dynamically identified and the patient can be sent immediately to the healthcare center for preventive actions. In the pervasive healthcare environment, such an arrangement is possible wherein patients can engage freely in their daily routine activities and also be monitored for ECG signals continuously. Capacitively coupled ECG (CC-ECG) is an alternative method in which an ECG signal is obtained without conductive contact with the patient’s body [43]. In this method, a thin layer of insulator isolates the human body from a metal plate electrode and thereby forms a capacitor. The electrodes can be applied to a cloth that can be worn by the person requiring continuous monitoring of ECG signals. The CC-ECG sensor-based ECG can be designed to be portable and small and can work wirelessly to support a pervasive healthcare environment. To enhance battery life, use of lowpower components including techniques like idle mode, low power wireless protocol, etc., are adopted.

6.1.4 EEG sensor Electroencephalogram (EEG) is a technique to measure the electrical activity of the brain of a person using small electrodes at multiple locations on the scalp [44]. It is a noninvasive method that can be applied repeatedly to patients, normal adults, and children without any risks. The electrical impulses are generated by nerves firing in the brain, having an amplitude in the range of microvolts (μV) and frequency between 8 and 50 Hz. EEG signals can be classified into the five bands of electromagnetic waves [45] shown in Table 3. EEG is sensitive to a variety of states ranging from stress state, alertness to resting state, hypnosis, and sleep [46]. Beta activities dominate when a person is in the normal state of wakefulness with open eyes. In a relaxation or drowsiness state, alpha activities are predominant. If a person feels sleepy, the power of lower frequency electromagnetic waves increases. EEG is used in many medical and nonmedical applications. Some of the medical applications are monitoring alertness, coma and brain death; locating areas of damage following head injury, stroke, tumor, etc.; investigating epilepsy and locating seizure origin; analyzing sleep disorders and physiology [46], and so forth. Among the nonmedical applications, EEG is used for the psychological training of sports persons, helping them to enhance focus and to have effective management of stress or fatigue. EEG can also be used for the study of cognitive processes, decision making, driver alertness, etc.

6 Different healthcare sensors

Table 3 Frequency bands, corresponding activities and state of the brain with the strength of EEG signal Activity

Frequency (Hz)

Strength (μV)

δ

0.5–3

100–200

θ

4–7

<30

α

8–13

30–50

β

14–30

5–20

γ

31–50

5–10

State of brain Deep sleep, unconscious, anesthetized or lacking oxygen stage of a normal adult. Adults don’t exhibit δ activity in a conscious state People experiencing emotional pressure, interruptions of consciousness, or deep physical relaxation Consciousness, quiet, or in mentally inactive awakeness (relaxed) state When a person is conscious and alert; thinking or receiving sensory stimulation This activity is related to cognition, perceptual activity, or selective attention

EEG supports the pervasive environment, as monitoring of the brain functions for various applications can be performed in an unconstrained manner by the participants performing normal tasks in the workplace and home. An EEG machine consists of electrodes, amplifiers, filters, and recording unit. Electrodes are usually placed on the scalp with good mechanical and electrical contact with the help of conductive jelly, following the international 10–20 based system. Dry foam electrodes, MEM sensors, microprobe electrodes, etc., are popular alternatives to wet electrodes for the ubiquitous environment. The electrical signal received from the electrodes needs adequate amplification followed by removal of noise, using amplifier and filter respectively. An analog-to-digital converter (ADC) is employed to convert the signal into digital form before feeding it to a computer for analysis and storage purpose.

6.1.5 Acceleration sensor Physical activity is regarded as one of the leading health indicators of the health status of a person, especially in the area of cardiovascular disorder, diabetes, and obesity [47]. Reduced physical activity indicates possible illness and symptoms related to functional impairment. Accelerometers are widely used as practical sensors for wearable or body-fixed devices in the monitoring of human physical activity [48]. They measure the acceleration of a moving object with respect to a reference axis. Use of accelerometers is preferred over other methods to measure physical activity, as acceleration is proportional to the external force driving the intensity and frequency of human movement. Velocity and displacement information can be suitably derived out of the accelerometer data. In addition, accelerometers can also provide tilt sensing, which is used to classify different postural orientations, detect falls, etc. [48]. Broadly, there are three types of accelerometers available in the market, namely

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piezoresistive, piezoelectric, and differential capacitance types [47]. Among the three, the differential capacitance type of accelerometer is popular and widely used in mobile phones and other portable electronic items, including health monitoring devices.

6.1.6 Pulse oximeter The oxygen level of blood is an important parameter in the human body. If the oxygen level is low, the human body may struggle to work properly, and very low oxygen levels may strain heart and brain. A blood-oxygen saturation (SaO2) reading indicates the percentage of hemoglobin molecules in the arterial blood saturated with oxygen compared to its maximum capable absorption value. In normal conditions, the value of oxygen saturation level is more than 89%. The pulse oximeter is a device used to measure SaO2 [49]. The measurement of SaO2 by pulse oximeter is termed SpO2. A pulse oximeter works on the principle that oxygenated hemoglobin (O2Hb) and deoxygenated hemoglobin (HHb) differentially absorb red and near-infrared (IR) light [50]. The O2Hb absorbs a higher amount of IR light and lower amounts of red light. Similarly, HHb absorbs more red light and less IR light. This difference is exploited by a pulse oximeter. It emits red light at a wavelength of 660 nm and near-IR at a wavelength of 940 nm using a pair of light-emitting diodes fitted in one arm of a finger probe, as shown in Fig. 2. The two lights transmitted through the finger are then detected by a photodiode on the opposite arm of the probe. Based on the relative amount of red and IR light absorbed, the oximeter computes the percentage of Hb bound to oxygen. Apart from the fingertip, the sensors can also be placed on the earlobe or the toe. In the ubiquitous monitoring environment, the signals collected from the sensor unit interface with a miniaturized processing unit, which in turn forwards the data to the healthcare establishment using wireless means such as WLAN, smartphone, etc.

FIG. 2 SpO2 sensor.

6 Different healthcare sensors

6.1.7 Heart rate monitor The human heart is responsible for pumping oxygenated blood and nutrients to different parts of the body and collecting deoxygenated blood containing carbon dioxide and other wastes. A cardiac cycle is defined as the steps involving the conversion of deoxygenated blood to oxygenated blood in the lungs and pumping it by the heart to the body through the aorta [40]. The frequency of the cardiac cycle is referred to as heart rate (HR) and is expressed as beats per minute (BPM). HR is a vital sign signifying mental and physical health of a person. HR for a normal healthy adult varies between 60 and 100 BPM. Lower HR at rest usually signifies better cardiovascular fitness and efficient functioning of the heart. A person having lower physical fitness usually has a higher HR. Various methods are available for measuring HR. One of the noninvasive and common techniques uses near-infrared light [51]. The sensor arrangement is identical to the pulse oximeter described in the previous section and works on the same principle. In the case of HR monitoring, the signal obtained from the flow of AC current is the important parameter. Hence it is intercepted, amplified, filtered and fed to a microcontroller for determination of the frequency of the signal. HR in BPM is obtained from the signal frequency value after multiplying by 60, which can be displayed in the LCD module and transmitted to the mobile network using a suitable wireless protocol for remote monitoring and storing. HR can be computed from the ECG signal by observing the periodicity of the QRS complex. Wrist wearable HR monitors are now commonly available in the market from a variety of manufacturing firms; these can be connected to the internet through mobile phones for storing and future analysis of data by physicians.

6.1.8 Cardiac rhythm monitor The heart of a person may beat too quickly (tachycardia), too slowly (bradycardia), or irregularly due to the malfunction of the heart’s electrical impulses [52]. Such a situation is referred to as heart rhythm disorder or cardiac arrhythmias. Minor cardiac rhythm disorder may be handled by simple lifestyle changes, whereas major disorders such as recurrent fainting, palpitations, unexplained stroke, or atrial fibrillation may be serious and life-threatening, therefore requiring immediate attention by a medical practitioner. Cardiac arrhythmias often occur in a transient manner and do not remain all the time; thus an ECG may not be able to detect such irregularity in the heart’s functioning. In such situations, the patient’s heart needs to be monitored over a period of time ranging from 24 h to 30days, or even for longer periods (years), and a cardiac rhythm monitor is used for such measurements. External and implantable/insertable types of cardiac rhythm monitors are available to record the heart’s electrical activity [52]. Holter and Event monitors [53] are the most common types of external cardiac monitoring devices, which are fitted with wires to the outside of a patient’s body for a shorter period. These devices record and store the cardiac data, which can be sent to the physician for analysis and diagnosis. Implantable and insertable types of monitors are designed for long-term use (up to 3 years) in situations where short-term monitoring cannot detect the heart malfunction. They have a small size and are placed under

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the skin of the chest. Implantable monitors are very effective in determining the causes of infrequent and unexplained arrhythmias. Data recorded in both external and implantable types of monitors can be transmitted to monitoring centers for review and report generation purposes. As an example, the mobile cardiac telemetry (MCT) system, which is a wireless-enabled arrhythmia event monitor, consists of a wearable monitoring device and a portable data transmission device [54]. Such devices permit pervasive monitoring of cardiac intermittent disturbances of a patient.

6.1.9 Pill camera Traditional endoscopy and colonoscopy procedures are carried out by doctors to examine the upper and lower portions of the small intestine to identify various diseases related to the gastrointestinal tract. The middle part of the intestine is not accessible by either of these procedures [55]. A procedure called capsule endoscopy, in which a tiny camera along with other accessories in the shape of the capsule, as shown in Fig. 3, is used to take images of the small intestine, permitting direct visual

FIG. 3 Pill/capsule camera [56].

6 Different healthcare sensors

examination [57]. Swallowing the capsule or pill camera helps to identify the source of gastrointestinal bleeding, detect bowel inflammation from Crohn’s disease, find tumors, or see ulcers. The pill camera, having an approximate dimension of 26 mm
11 mm, contains a small digital camera, a light source, one transmitter antenna, and a battery to power it up. The pill is capable of transmitting two images per second wirelessly for storing in a data recorder worn as a strap around the waist by the patient. These devices can provide a 140–170 degree view with a battery life of 6–8 h. The images can be viewed with the help of dedicated software in a computer at a variable speed, almost like a video [57]. A patient can continue his routine activity after swallowing the pill cam and placing the data recorder around his waist. He may return to the healthcare center after 6–8 h for downloading and analysis of the images. In the pervasive healthcare environment, the recorded images may be accessed remotely through the mobile internet using a smartphone [58] by the physician for examination, without the need to visit the hospital for the patient.

6.2 OTHER SENSORS USED IN MEDICAL CARE UNITS 6.2.1 Room temperature sensor An elevated room temperature may produce an environment that is not conducive to sleep continuity of a patient inside a healthcare facility. In addition, it may produce an adverse effect on the rehabilitation process of a patient. Maximum temperature recommended for healthy sleep is 24°C. Therefore, in healthcare centers, a robust automatic continuous temperature control system should be in place. Sensors are deployed at regular intervals to sense the temperature levels at different places in the healthcare unit. Temperature data from these sensors are transmitted to a central control room wirelessly. Based on the information received, the control room may transmit an appropriate corrective signal to the cooling device to adjust the temperature to the desired value.

6.2.2 Barometric pressure sensor Barometric pressure measurement systems are used in hospitals to measure room pressure and to verify proper airflow in patients’ wards and cabins. In addition, this equipment helps to ensure the safety of patients and medical staff, keeping the airborne pathogens away. Microelectromechanical system (MEMS) sensors are widely used to measure barometric pressure. In addition, MEMS pressure sensors are used as inhalers to monitor the incoming and outgoing pressure of blood.

6.2.3 Light sensor Illumination in medical care units is one of the important parameters to be maintained, as increased light levels create an environment unsuitable for nighttime sleep. The recommended light levels by the Illuminating Engineer Society for hospital rooms are between 10 and 20 lm/ft2. Reduced power consumption is another important benefit of controlled illumination. Usually, the luminaire used in a controlled

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lighting system contains an occupancy sensor and a light sensor [59]. These sensors are connected to a central controller through networking. The occupancy sensor identifies the presence of a person within its coverage area. The light sensor computes the total illumination obtained from daylight and the luminaries within its vicinity. The illumination and occupancy information so obtained is then forwarded to the central controller, wherein the appropriate decision regarding the dimming level of artificial illumination is made, with the help of a lighting control algorithm. The computed dimming levels are then transmitted back to the corresponding luminaries to correct their illumination levels.

6.2.4 Motion and activity sensor Physical activity of a person is one of the important parameters of good health. In addition, the mobility of a patient is an important factor to be carefully monitored during the rehabilitation period in a hospital. Conventionally, a pedometer, actometer or accelerometer are the preferred sensors used to determine the motion and physical activities of a person. A pedometer counts each step by detecting the motion of a hands-on-hips. The distance traveled by the person may also be determined with the help of a GPS receiver. Actometers are capable of recording acceleration and intensity of movement. Recent research shows the identification of different body postures like sitting, lying, and walking [60] is also possible to enable a new ambulatory measurement system, especially for elderly patients. Miniaturized kinematic sensors are placed on the person’s chest to detect such postures. In addition, detection of the postural transition between standing, sitting, lying, and locomotion activities during standing has been facilitated by the sensors.

6.3 DIFFERENT FITNESS DEVICES Wearable devices, empowered by smart sensors, have elevated modern healthcare support through continuous monitoring of physiological parameters. Devices like pedometers, activity trackers, etc., with the help of various fitness apps, are controlling the way we exercise and maintain a healthy lifestyle with suitable and timely instructions and motivation. For example, sportswear with a smart sensor allows us to improve our performance by forging body data into training advice. Below, a few examples of such fitness devices are discussed.

6.3.1 Wrist band The advancement of health monitoring sensors has brought commercially usable wristbands. This wristband, also known as an activity tracker or fitness tracker/band [61], assesses a person’s physical activity and tracks the health and other vital statistics. The fitness tracker monitors 24/7 heart rate, steps, sleep, stress, VO2 max, calories consumed, etc. These devices, along with monitoring, also enable wellbeing and staying healthy by advising for exercise, dieting, and sports coaching [62]. The fitness tracker monitors one’s health and activity effortlessly using noninvasive sensors in an efficient and very accurate way. The fitness tracker can be synchronized

6 Different healthcare sensors

with a smart mobile device, reflecting the person’s health status. Mobile intelligence applied over one’s past data could provide timely and appropriate health advice.

6.3.2 Eye gear The health and wellness care industry have come up with eye gear that helps the user with health updates while performing swimming, cycling, and other very fast body activities that demand constant health monitoring. The eye gear constantly monitors one’s activity pace, heart rate, cadence and power, etc. The person’s health statuses are projected on the glasses and aural prompts are made through the earpiece; this avoids having to look constantly for health and activity status as with other fitness devices such as smart mobile devices and wristbands [63].

6.3.3 Smart shoe Smart shoes are a new kind of shoes that help in keeping track of physical fitness. These smart shoes can be slipped into very much like a normal shoe, without the bother of wearing extra accessories like a fitness band, making the health and physical tracking quite invisible. The fitness tracker is put into the sole of the shoe to assess the running metrics of an individual. The stored data can later be synced to the mobile device for analysis. These shoes are very useful for preevent training [64].

6.3.4 RFID tags The simplicity of Radio Frequency Identification (RFID) in terms of operability, wireless sensing, and lower cost has made these tags a popular technique for tagging any object, thereby connecting it to a virtual system. RFID tags principally work on radio wave based identification and tracking technology. The system consists of tags that are identifying devices, readers, or a base station and underlying information system. Commercially different frequency ranges of radio waves have been found in use by RFID tags for communication with reading devices. The tag transmits its ID using an RF signal, which is read by a reader or multiple base stations while in close proximity. On the basis of the usage of an external power source like battery power, the RF tags can be categorized as active or passive [65]. An active tag uses external battery power to transmit a signal and hence it has more transmission power and coverage range. A passive tag uses the received signal’s power to boost up and send a modulated signal back, thus having limited transmission range. The distinctive properties of RF signals that make them ideal for identification tracking are: • • • • • •

Traverses through walls Does not require direct transmission path or line of sight Operating range up to 30 m or more High speed Uses low-power transmission Supports data rate up to 1–2 MBPS

RFID has contributed to IoT in reaching practical heights. The application of RFID in the medical and healthcare sector ranges from information management to patient

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monitoring. Though RFID actually does not return direct patient health data, it successfully allows connecting things (living or nonliving) over the Internet and thereby orchestrates various action, operation, and management in an efficient manner. In medical and healthcare services, some examples of RFID as an enablement of IoT are [66]: •

•

•

•

•

Patient information management: Patient health records containing medical history, ailments, type of treatment undergone and side effects, medication, or medical examinations stored in the database can be linked to RFID. Doctors and nurses administrating the patient can get the details from the patient’s RFID tag, which would help in proper diagnosis and preventing wrong medication from being delivered. Information sharing: RFID system helps to create a strong network for sharing medical information or records. Patients’ medical information, stored in the database, is linked to RFID tags. This ensures doctors can skim through the patient’s medical records, medical history, treatment procedures and information, insurance coverage, etc. The application of RFID helps the patient to suitably choose doctors and hospitals. The information stored in the database can be well shared among doctors, regardless of space and time. This also ensures the doctors and hospitals are constantly updated with new progress. Constant real-time monitoring: In medical research and production, RFID tags are being used to monitor the entire research, production, and distribution of medical products like medicine and others. While circulating, the users are informed of all the details of medication, thus maintaining quality. If the quality of medication is suspect, all information like name, category, origin, batch processing, delivery, and sales can be traced back. Medication storage management: RFID tagging system helps to maintain the medical stock, thus reducing manual input error. The RFID systems to maintain stock further help in avoiding name confusion in cases where the medicines have similar names, and also help with stock level maintenance, timely supply of medicine, and reordering. Medical equipment traceability: Medical equipment linked with RFID tags helps to know what the device is, its origin, period of use, quality issues, what patients have used the equipment, places where the equipment has been used, and used/unused status.

7 BENEFITS OF CONNECTED HEALTHCARE It should be noted that IoT has changed the definition of the healthcare concept for today’s world. Not only patients but also health experts around the world are acknowledging the undeniable contributions of IoT in healthcare. From personal fitness to surgery, IoT is providing remarkable efficiency, resulting in more integrated healthcare. Following are some key benefits of connected healthcare:

7 Benefits of connected healthcare

Patient engagement and care management: With IoT, people now have personal health information and care at their fingertips. IoT-based applications allow patients to access their own health data and thus have a lucid picture of their health improvement. The goal is emancipating someone to be energetic in their own care, by allowing them to continuous monitor of their own health data like blood pressure, glucose level, body temperature, calories required, and many more. The IoT-based attached sensor accesses vital statistics on personal health and can feed instant advice through a mobile device. Further, when needed, the patient’s condition is analyzed to send major alerts with all necessary health data to the nearest health center so that imperative steps can be taken for the patient’s care. Real-time data: In many cases, like an accident or sudden health problem, swift action is required to save the victim’s life. For physicians and health experts, the lack of real-time health data for a victim, such as current heart condition, blood pressure, number of fractures, blood loss, internal hemorrhage, previous health complications, etc., has made urgent emergency services very difficult. Being able to assess the vital statistics of the patient in real time is essential. The application of IoT makes this job easier for medical and health professionals by providing the necessary real-time patient data. IoT sensor devices like a body scanner or a watch attached to the patient’s body can collect the real-time vital statistics, and the real-time data analysis could help the health experts to provide accurate and quick treatment to the patient. Elevated treatment outcomes: Proper diagnosis of any health problem is the key to better and improved treatment and this is possible only when there are adequate statistics regarding the patient’s past health records and continuous collection of real-time health data. Through the huge number of connected devices, healthcare experts can access a large amount of real-time data, helping them to analyze healthcare trends and also measure the effects of any particular medicine or health condition over time. Quick and meaningful response to emergencies: An IoT sensor device’s continuous monitoring and assessment of patient health statistics and analysis of realtime data can help the caregivers in getting meaningful health alerts when needed. Analyzing and accessing the real-time data for any deviation beyond the threshold in health parameters draws the attention of health experts, thus bringing faster and appropriate medical service. Admittedly this could save a life. Better care for the remote patient: Lacking or inadequate medical and healthcare facilities and services in remote places make it difficult for patients in continuing treatment; it is true that patients living in remote locations have great difficulties in visiting their doctors. Similarly, for health experts, it is very difficult to visit patients in remote places. With the development of the ingenious approach of IoT in medical aid and services, diagnosing and caring for patients has been made much easier for health experts as well as for the remote patients. Now the doctor can monitor their ailments and other health parameters more accurately from a remote location by connected medical devices. The continuous collection and analysis of real-time health data from those remote areas help health experts to make quick and meaningful responses.

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IoT for persons with a disability: Leading a normal life can be difficult for a person suffering from paralysis, polio, leg or arm amputation, muscle and nerve problems, blindness, hearing issues, cognition problems, etc. For over a century, efforts have been made to overcome the challenges faced by persons with disabilities. In this regard, the development of sensor-based IoT devices has helped in enabling these people to overcome their disabilities. For example, advanced sensors have brought sight and sound to blind and deaf people, respectively. Sensors assessing the patient’s brain and nervous system, such as EEG devices, can help people in a wheelchair or bedridden persons suffering from paralysis, muscle disorders, and cognition problems to have real-time interactions. Devices like cameras, proximity sensors, etc. can help to realize the context of persons and their surroundings, thus helping blind persons as well as persons walking with the help of robots to understand their surroundings. The different IoT-enabled devices have brought new hope and capabilities to many persons with disabilities. IoT as error reducer: One small error in a health report can lead to a formidable accident in anyone’s life. With IoT, we can reduce the scope of medical errors where IT plays an important role. More accurate data, automation, and analytical decisions are some important characteristics of IoT helping in reducing errors. Smart medicine: Worldwide healthcare costs are rising so rapidly that healthcare will be unaffordable for ordinary people in the coming future. Rapid innovations of new technology in the health industry have brought some hope for overcoming this situation. Unprecedented devices allow patients to test their own saliva, blood and even nasal fluids for medical ailments. Specialized footwear fitted with sensors monitors changes in walking patterns, which can be a sign of a serious medical condition. Medicines with ingestible sensors gauge whether the patients are taking the medicines as prescribed by their doctor. Along with the diagnosis for treatment, IoT also allows preventative care without the need for lengthy and costly visits to clinics or hospitals. From drug-free pain relief options to smart stethoscopes that can send heart and lung sounds to a chosen host device for further analysis, this innovative technology can save both time and money. Cost reduction: Availability of real-time data not only helps in remote monitoring of patients but also reduces healthcare costs, as doctors or other health experts need not visit the patient physically to collect the health data for diagnostics. Further, patient monitoring can be carried out on the patient at home or in a remote area instead of the hospital, thus saving hospital costs. IoT allows sharing of the patient’s health data among hospitals and doctors while the patient shifts from one hospital to another as needed. This eliminates redundant diagnostic testing and treatment procedures every time the patient visits a new health center. One of the unique features of IoT-based healthcare services is that it enforces preventative healthcare. The healthcare sensor assesses the patient’s present health conditions, which on being further analyzed can predict future health complications and ailments. This future health prediction can help the patient and healthcare expert to take preventive measures, thus avoiding the future health complications and hazards and their associated costs.

8 Challenges in connected healthcare

8 CHALLENGES IN CONNECTED HEALTHCARE This section explores some of the major challenges that need to be met in order to reap the optimum benefits of pervasive healthcare. Data collection and management: Nowadays, due to the data explosion, data collection and management are challenging to deal with. A huge amount of data is being continuously generated by IoT devices. Some smart devices store the data for a certain period or send it to the governing components. Devices send the data to collection points using wireless technologies like Wi-Fi or ZigBee. Most of the time, these data come in as unstructured data, as they are generated from different devices. These data need to be preprocessed to identify missing data, remove redundancies, and integrate heterogeneous data in a structured manner. Collecting and storing different types of data from diverse devices is truly challenging. Several solution approaches are being proposed and adopted by industry. Microsoft has developed Health Vault, which acts as an EMR (Electronic Medical Record). REshape Innovation Center of Radboud University Medical Center has developed HereIsMyData [67], a database solution that enables patients to store their own medical data. Other products from Fitbit, Apple’s research kit, etc., provide users’ medical data to researchers, where it can be used to test fitness, nutrition level, disease progression, etc. Later, the preprocessed data are stored in order to get further insight by analyzing this data and predicting future health conditions or to detect abnormalities in the data that may initiate further investigation. Data overload: Various IoT and connected medical devices used in healthcare produce an enormous amount of data. The rate at which data are produced is huge. It scales up with time and an increasing number of patients, putting major pressure on the network and a burden on the data storage and access process. Furthermore, processing such voluminous data for medical analysis with accuracy is an overloaded operation, and may cause a delay in receiving appropriate feedback, ruining the very essence of the pervasive healthcare philosophy. This constraint demands a new form of data transmission, storage, access and processing. Data and device interoperability: Patients are fitted with different kinds of sensors and medical devices. The data produced by one device might be used by another device as an input for further actions. These devices are often from different manufacturer and may generate data in different formats or structures, production rate and data interfacing media connection. Often the same kind of sensor from different manufacturers produces data in a different format or data rate, or they have different physical interfacing for data communication. This introduces the interoperability issues which make it difficult to work with different devices cooperatively. Lack of standardization: As mentioned in the previous paragraph, devices and applications from different vendors may not be compatible with each other. This can lead to situations where data produced by one device may not be meaningful to other devices since they cannot interpret it. Buying the complete healthcare solution including all the devices and applications from a single vendor may not always be a wise option, both technically and economically. Also, this might promote a particular

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vendor to monopolize the market which will ultimately increase the cost. To avoid this, there is a need for standardization of the medical devices including their operations and the data format and structure. Due to the lack of any benchmarked standard, device integration is a real issue. Though, recently, some IoT healthcare products are providing data in a standard format which is interoperable [68]. The inadequacy of system integration: Often patients are asked to use multiple implantable and wearable devices to collect health data. Usually, these devices work in an individual capacity and are often isolated and transparent to each other, mainly because different device vendors provide data access only to their own device or cloud. This practice sometimes negates the cause; i.e., the collected data become useless until they are correlated with other data. For example, suppose blood pressure information is collected continuously from a patient who is suffering from hypertension and it is reported to the physician, while at the same time another device is working to detect his chest pain. In this case, both sets of data are needed to get the true picture of the patient’s health. IoT device vendors do not allow other devices to access their collected patient data and keep those data limited to the system or application. Due to this data locking, data is not always visible to other systems, which reduces the potential value of the whole healthcare system. Also, the data collected from different medical devices are generally not transferred to a centralized system and, in most cases, they are not easily available due to the scattered depositories. This diminution of information reduces the accuracy level of any analysis. Lack of integration of medical data and contextual information: It is undeniable that IoT has paved the way for collecting medical information from patients that was difficult to collect earlier. But this information often becomes less valuable if it is not perceived contextually. A variety of clinical data are collected from various sources but most of them are siloed. Incorporating them with the contextual information (e.g., patient’s medical history with exact timeline) would actually bring the true benefits of a connected healthcare system. As mentioned previously, most often the collected data are confined to the device vendor’s data depot or to the specific application only. For physicians, the isolated data are not as useful as they would be in combination and in the context of the patient’s overall medical record. Anomalies in sensor data: Removing anomalies in sensor data is one of the big challenges in the healthcare system, as such anomalies may deter a proper diagnosis. Several algorithms have been proposed in order to remove anomalies from sensor data. But, it is of more importance to define what can be categorized as an anomaly for each device. For example, suppose a patient has experienced some heart pain and is monitored by an ECG sensor showing the status of his heart health. During his exercise session, his heart rate temporarily increases to more than the normal heart rate. If the ECG sensor considers it an anomaly in the heart rate reading, the diagnosis can be erroneous. Managing IoT devices: Several different kinds of sensors and smart devices are used in medical diagnosis and clinical care. The number of devices that are being introduced is increasing continuously and managing these devices is challenging. For example, devices from different companies require a different kind of software

8 Challenges in connected healthcare

update, which creates a burden on the IT team who have to know about different maintenance procedures, which can be quite cumbersome [69]. Several companies are providing a platform to solve the problem of managing IoT devices. For example, Intel provides secure transmission of information from different connected IoT devices [69]. Another solution is to automate the IoT devices management task. This will keep IoT devices up to date by continuous monitoring of the device condition. Data security and privacy: Like any networked system, connected healthcare is vulnerable to security threats. As medical data is related to lives, it is of utmost importance to secure sensitive data. The connected system will create opportunities for the unauthorized hands of ill-intentioned users to reach the locked data. Leaking of private patient records may prove to be some of the biggest failures of connected healthcare. In the traditional healthcare system, vulnerabilities were restricted to the hospital area where such information was kept. Now, in the e-healthcare system, information is stored on multiple servers, which may be susceptible to attackers [70]. Three major security issues are (see Fig. 4): • • •

Monitoring patient data Analyzing traffic Identity theft that affects the healthcare system

In the case of monitoring patient data, an attacker can easily access patient information by snooping on the data. Sometimes, attackers misuse this sensitive information in unpleasant activities. Though the data is encrypted during transmission, there is a possibility of revealing information patterns. In the identity theft process, the attacker impersonates the patient and uses their confidential and sensitive data. It is more valuable to criminals who can wrongly use the data for blackmailing patients. Criminals can use patient’s data in order to commit fraud, for example, fraudulent

FIG. 4 Privacy issues in healthcare.

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insurance claims in the patient’s name. Sometimes lack of privacy can reveal sensitive information of the user to the attacker. For example, a fitness tracker displays the heart rate of the user to encourage them to exercise more. But if this information is altered (showing a lesser heart rate than actual), this might be severely harmful to the patient’s heart. Lack of common security standards and practices over the data transmission technologies is a major concern. Organized healthcare entities like hospital authorities and device manufacturers play a major role in medical data security. Hospital authorities need to ensure a secure environment by adopting authentication, etc. An efficient authentication system, such as biometric log-in, should be installed in order to restrict unauthorized access to patient data. The device manufacturer also needs to maintain some security standard on their devices. A regulatory system such as HIPAA (Health Insurance Portability and Accountability Act of 1996) has been proposed in order to ensure restrictions on what medical information can be transmitted, stored, and displayed [71]. Another basic security practice is encryption. This should be applied to stored data (hardware-level encryption) as well as in-transit data. To reduce the chances of sensitive data being stolen, data transmission encryption is important. Many hospitals ensure secure patient data storage but don’t have the security of data during transmission [72]. Some networks provide strong end-to-end security but some networks such as wireless LAN are unsafe. An attacker can steal information by analyzing the packets. In spite of significant advances in network security, end-to-end security is still a major issue [70]. The security threat needs to be taken care of by injecting rich authentication mechanisms, providing a powerful encryption algorithm. The latest and strongest security solutions need to be adopted (e.g., BLE security, one of the popular wireless standards that provides secure transfer of data). Passive eavesdropping is one of the serious issues at the time of data transfer, when a third party listens to the data exchange between the two paired devices, and this issue has been thrashed by BLE using AES-CCM cryptography [73]. The problem of healthcare data security has been made even more critical in the wake of widespread ransomware and cybersecurity attacks on healthcare systems.

9 HEALTHCARE APPLICATIONS OF SMART SENSORS AND IoT Smart sensors along with the connectedness of IoT have created a plethora of new opportunities. Many innovative and high-end applications have emerged that leverage the capabilities of modern healthcare devices, such as sensing, tracking, and mobility, to achieve an overall pervasive healthcare system. These applications may range from remote and real-time monitoring to smart diagnosis and medication. This section mentions some of the exciting smart medical devices and discusses their functionality. Table 4 summarizes a few of this kind of device, highlighting their limitations and challenges.

9 Healthcare applications of smart sensors and IoT

Table 4 Smart medical devices Device name Smart Needle

Application

Functionality

Analyze and identify blood vessels or tissues in brain surgery

Guide to find the accurate operational location ensuring safety

Processing focus Image, audio signal

Limitations and challenges

• Late • • •

iTBra

Detect breast cancer

Detects any thermal abnormalities, tissue elasticity

Temperature, tissue pattern

•

• CADence System

Detects coronary artery blockages

Detect coronary blockage

Cardiac sounds

• • • •

UroSense

Urine monitoring

Measures CBT (core body temperature) and urine

CBT and urine

•

Digital Pill

Proper use of prescribed medication

Tracks the pill ingestion time, activity level, monitor the sleep pattern

Stomach fluid electric signal

• • •

transmission of audio signals The flush back of blood was very slow Loss of signal Few manufacturing challenges Diagnosis depends on the underlying assumption, for predictive analysis, which has to be accurate Invades patient’s privacy Patient’s data accuracy Functional data depends on patient’s state Anatomic limitation Data processing time is too large for the severe condition of the patient Works accurately only when the rate of production of fluid coming out from patient’s body is smaller Data privacy Patient-doctor relationship Less face-toface interaction with the doctor

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9.1 SMART NEEDLE Brain surgery is considered to be one of the most intricate surgeries in medical science. Researchers at the University of Adelaide in South Australia have invented a “smart” needle with an embedded camera, which is now helping doctors to perform safer brain surgery. A probe with the size of a human hair uses an infrared light to look through the brain [74]. It uses the concept of IoT to inform the doctors of any abnormalities. The smart needle uses software to take a picture, analyze and decide if it is viewing blood vessels or tissues. The successful trial of this needle with a 200-μm wide camera was carried out with 12 patients at Sir Charles Gairdner Hospital [74]. According to the head of that trial, Professor Christopher Lind, “It will open the way for safer surgery, allowing us to do things we’ve not been able to do before.” But for effective use of smart needles some of the associated challenges, as mentioned here, should be handled [75]: • • • •

The smart needle is not useful for easy cannulation, the cause of late transmission of audio signals. Due to the presence of an ultrasonic probe within the lumen of the smart needle, the flush back of blood was very slow. Presence of air bubble in the needle causes loss of the signal. It needs to flush the needle using saline water. A few manufacturing challenges occurred, such as a stiff Luer lock on the probe, which has been rectified by the manufacturer to a Slip-fit lock.

9.2 iTBRA Even after significant advances in medical sciences, cancer still is a serious menace. The modern lifestyle has aggravated the possibility of suffering from cancer. Over 508,000 women died in 2011 due to breast cancer [76]. It has been observed that most casualties are due to the lack of early detection and awareness. With early detection, smart sensors can play a significant role. An innovative cancerdetecting bra, called the iTBra, has been devised by the scientist and entrepreneur Rob Royea. The iTBra (Fig. 5) is a smart device that can detect temperature changes in breast tissue. The data sent by that device helps the healthcare experts to evaluate the risk of breast cancer. It works effectively for women with dense tissue for which it is difficult to detect cancer using mammograms. The iTBra uses machine learning and predictive analytics to identify and classify abnormal patterns that are important for early breast cancer detection [78]. More importantly, it is claimed that the iTBra needs to be worn for only 2–12 h once a month and there is no painful squashing or prodding or radiation involved [78]. The iTBra uses a predictive analytics concept to predict breast cancer and it is well-known that all analytics, especially predictive analytics, rely on some

9 Healthcare applications of smart sensors and IoT

FIG. 5 iTBra [77].

preassumptions. If the underlying mathematics is not correct or the assumption is not rightly mapped with the reading and the decision, it can wrongly diagnose cancer. Another negative aspect of the iTBra is that it invades the privacy of the patient.

9.3 CORONARY ARTERY DISEASE AND IOT CADence (Fig. 6) is a noninvasive, radiation-free, exercise-free, acoustic, ECG and artificial intelligence-based handheld device, manufactured by AUM Cardiovascular. It aims to provide information regarding cardiovascular conditions, including ruling out significant coronary artery disease, heart valve disease, congestive heart failure, ventricular compliance, cardiomyopathy, and arrhythmia with the help of advanced analytics. It uses IoT global connectivity provided by AT&T to deliver test results to clinicians within 10 min [79]. The technician uses the device to collect data

FIG. 6 CADence [79].

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from a supine patient from four different thorax locations; then after receiving the data from the device, the AT&T Global SIM card sends the data in a very secure way to AUM’s secure server for pattern analysis. Within 10 min, the health experts receive the result via email; the whole process, from patient data collection to final results, takes less than 20 min to complete. CADence has some limitations, such as it performs a global assessment and cannot be used to identify abnormalities in specific vessels/valves. Also, the specificity and positive predictive value (PPV) is low. Moreover, the 20-min turnaround time might be too long depending on the severity of the patient’s condition.

9.4 PERSONALIZED MEDICAL CARE Proteus Discover, a revolutionary invention using IoT in smart medicine (digital pill), has changed the concept of personalized treatment plans by enabling continuous assessment of health data. According to Dr. Purvance, CEO of Barton Health, many patients struggle with medication adherence; due to their nonadherence to medication schedules and dosages, they do not experience positive outcomes from the medicines while the doctor thinks that the patient is taking the medication as ordered; that can lead to unnecessary changes in treatment plans and may increase the cost of treatment [80]. As a solution to this kind of problem, a grain-of-sand size ingestible sensor can be provided to the patient along with the medicine; when it reaches the stomach, the sensor communicates with a sensor patch attached to the patient’s body. The patch keeps track of ingestion and personalized data of the patient such as heart rate, activity, etc. The collected data then is disseminated through a mobile application to the patient, which allows them to share the data with a health professional for personalized treatment plans. In another example, the Future Path Medical UroSense Essential System [81] (Fig. 7) has revolutionized urine management through protecting the catheterized patient’s safety. UroSense uses a low-cost fluid sensor, an optional thermistor-based catheter, software, and wireless communications to create intelligent urine monitoring [81].

9.5 PATIENT MONITORING At Florida Hospital Celebration Health, family members of the patients being operated on need not depend on a doctor or nurse to let them know when their loved one is out of surgery. The RTLS (Real-Time Location System) keeps track of the progress of the patient from the pre-op room to the surgical unit to the recovery unit. A tabletgenerated screen with individualized identification numbers helps the family members to identify the patient in line with the privacy and security recommendations of HIPAA (Health Insurance Portability and Accountability Act of 1996). Patients always want more interaction with doctors; the RTLS system provides this facility to the patients, which makes them more happy and confident.

9 Healthcare applications of smart sensors and IoT

FIG. 7 UroSense [82].

9.6 CARDIAC RHYTHM MONITORING Today’s busy and unhealthy lifestyles stealthily cause damage to our hearts. Continuous heart monitoring is highly important, as cardiac rhythm is one of the key parameters for early detection of any abnormality in the heart. An IoT-based heart rhythm monitoring system is proposed in [83] that can study the blood flow volume in the human body, which is important for collecting pulse rate and BPM. The whole procedure is executed by a PPG (photoplethysmographic) system sensor [84]. It transforms the intensity of reflective light obtained inside the photoresistor to a waveform signal. The system then uses its algorithm to analyze the result and send a necessary warning message to the patient/doctor.

9.7 CARDIAC REHABILITATION Postsurgery care and monitoring of heart patients is important for fast healing and complete recovery, both physically and mentally. Cardiac rehabilitation is an environment where continuous monitoring of ECG signals at the time of physiotherapy helps the patient to manage their condition. The recognition and categorization of ECG arrhythmias is the main important achievement of this ECG monitoring system, which has a considerable significance in appraising and envisioning ventricular arrhythmias that can be life-threatening [85]. This type of system generally has three components: (i) a transmitter that transmits the ECG wave signals, (ii) a receiver that receives and intercepts the signal, and (iii) the central station with installed software that processes the signals, analyzes them, and instigates the audiovisual alarms.

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9.8 HANDLING COPD PROBLEMS According to WHO, by 2030 COPD (Chronic Obstructive Pulmonary Disease) will be the third leading cause of death in the world [86]. It is one of the critical types of lung disease caused mainly by smoking and the effect of some abnormal weather parameters (e.g., heat and humidity) [87]. Rising humidity in the weather makes the air denser, which is also a major factor in shortness of breath. Not only that, the presence of different pollutants makes it worse for the patient with COPD. IBM researchers in Zurich in collaboration with the Swiss start-up docdok.health [88] are in the process of developing an IoT-enabled system, integrated with multiple sensors, that can measure the different weather parameters and send a warning to the patient accordingly. It may also collect various health data like cough intensity, the color of sputum, heart rate, and breathing rate and send them to the server for analyzing with machine learning algorithms to establish the format and connections and also to recognize the progressive status of the disease [85].

9.9 SMART CONTACT LENS FOR DIABETICS Another innovative medical use of IoT will be a great relief for diabetic patients. A group of researchers at UNIST, South Korea, have come up with a smart contact lens that can substitute for the traditional glucose testing method [89]. This device, with built-in malleable limpid electronics, can detect the glucose level from tears. The lens is embedded with electrodes made of translucent and stretchable materials and the glucose sensor can transmit the electrical signal to the LED through a wireless antenna. After sensing the glucose concentration (above a certain threshold value) in the tears, the activated LED pixel turns off. During this whole operation, the smart technology of the lens maintains steady eye temperature without instantaneous heating. The data received from the sensor is then processed and analyzed and necessary alerts are generated.

10 USE CASES 10.1 MISSISSIPPI BLOOD SERVICE: MAINTAINING LOGISTICS SMARTLY Many healthcare organizations are using RFID to manage their inventories. For example, Mississippi Blood Service (MBS), a not-for-profit organization, uses RFID for tracking the bags containing blood and different blood components [90]. According to Gulam Patel, Manager of Information Services for the Jackson-based organization, accuracy in blood transfusion is one of the major life and death factors; the smallest error may have a huge penalty. Normal blood components have a life cycle of 5–42 days and for frozen plasma, it is 1 year. So, for MBS, supplying blood to different health centers throughout Mississippi as per their requirements was a major challenge. To maintain this huge logistics operation, MBS, along with AARFID,

10 Use Cases

a firm located in Eden, N.Y., tried to recognize the blood packets using RFID interrogators and the tags that attached to blood bags. But they experienced the following challenges: • • • • •

Interference caused by a metal tray that contained the blood bags. Interference caused by mobile phones. The density of water in the blood. Chemical components of blood. Unable to develop smart levels.

As a solution to these problems, they substituted the metal trays with plastic and restricted the position of mobile phones. To remove the retuning effect on the RFID transponder of chemical components of blood, MBS consulted with Texas Instruments. They realized that the transponder needs to be initiated at 14.4 MHz and immediately needs to be dropped to 13.56 MHz to overcome the problem. The whole process was controlled by AARFID software, which includes controlling a printer-encoder, interrogator, tag data, check-in and checkout of blood product, emergency trace recall of health experts, order entry, order fulfillment, and packing and shipping.

10.2 FINDING TREATMENT FOR COPD COPD is one of the major lung problems, causing the death of three million people around the world each year. A Spirometer is a device by which the COPD problems can be diagnosed and treated by measuring the in and out air flow of the lungs. But due to the high cost and unavailability of this device, the benefit could not be passed on to the patients with COPD. Shwetak Patel, professor of Computer Science and Engineering at the University of Washington and also a MacArthur Fellow, solved this problem by applying the concept of IoT [91]. Realizing the increase in smartphone users, Patel and his team developed an algorithm for measuring the sound of someone blowing on the microphone of the smartphone. The system scrutinizes the input and the attached devices send the results to the corresponding patient. A revised version of his algorithm works on any mobile phone, and is not limited to only high-end smartphones. This concept acts as a clone of the spirometer, which reduced the cost of diagnosis of COPD, and the easy accessibility of Patel’s device helped more people.

10.3 LAHEY CLINIC MEDICAL CENTER: TRACKING HEALTHCARE EQUIPMENT IN REAL-TIME A bigger hospital means more patients, multiple departments, and more healthcare staff, including doctors, nurses, technicians, and operators. When a hospital promises to provide top quality service to the patients, then there should also be advanced equipment along with trained staff for handling it. Today many hospitals maintain smart and improved medical equipment, but a major challenge faced by the staff

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is tracking the location of the equipment when they actually need it and also the proper maintenance of the equipment. Often health personnel cannot locate equipment when needed and as consequence there is a delay in the treatment and medical tests. This not only affects patients but also affects the goodwill of the hospital. Another adverse effect is that sometimes the staff place a requisition, assuming a shortage of that equipment, which causes an extra expenditure for the hospital. These challenges and consequences have been experienced by Lahey Clinic Medical Center in Burlington, Massachusetts, one of the renowned medical facilities in the Boston area. They realized that there should be a proper tracking and monitoring facility to overcome those challenges. Lahey Clinic Medical Center then consulted with GE Healthcare, which was actually working with another company called PinPoint, to unfold the concept of RTLS (real-time locating system) with active battery-powered RFID tags [93]. The Clinic personnel have positioned the interrogators in a proper location connected with more than 500 mobiles. The software installed on those mobiles easily detects the position of the medical devices in real time and sends the information to the staff. Fig. 8 explains the overall workflow of the RTLS system.

Location management

Enterprise WLAN Intranet

Enterprise RTLS visualizer RTLS tags XML API output/query

XML

Viewing

Reporting

Alerting

Web/text based

Historical/rule based

Email/pop up/text messages

FIG. 8 Workflow of RTLS system [92].

10 Use Cases

10.4 IRIN GENERAL HOSPITAL: IMPROVING HEALTHCARE QUALITY Experiencing the challenges of handling the huge amount of patient data generated in real-time and storing it, while maintaining accuracy and integrity, many traditional hospitals have transformed themselves into a smart hospital by digitalizing the whole medical system. Northern Taiwan-based Irin General Hospital, serving for the last 18 years, is emphasizing two major parameters in this smart transformation [94]: first, improving the healthcare quality of the local people by providing better access to professional healthcare services, and second, creating a friendly working environment by reducing redundant and unnecessary paperwork of the healthcare staff so that they can spend more time with the patient. One of the major challenges that they experienced before the smart transformation was the problem of batteries running out due to the heavy mobile medical card. When the battery ran out or malfunctioned, the entire nursing work had to stop until it was replaced. Venus with Intel Inside brought an all-in-one solution for this problem by providing high-performance energy efficiency with lightweight character. It also has two batteries backing up each other and also reduces the weight by 20%. For providing the best service to the patient, the hospital also installed the Onyx smart power bank, which offers an uninterrupted power supply and platform for distant electronic medical records management. The patient flow management system employs a smart whiteboard; when any health professional clicks on any item on the board, a standardized handover process connects it to the EMR and historical medical records and it is constantly updated through Wi-Fi, so the most updated patient status can be accessed. To improve the patient’s quality of life, the hospital also has deployed infotainment Onyx terminals where the patient has access to the Internet, online videos, and music. They even can order a meal, view health education videos, their medical image, treatment records, and also the prognosis of their treatment, etc. In this way the smart hospital is providing the smartest treatment facility for the smart patients by using smarter technologies.

10.5 JEFFERSON UNIVERSITY HOSPITAL: PROVIDING COGNITIVE ENVIRONMENT OF CARE When we get sick, we go to the hospital. Although hospitals can be a lifesaver for us, staying in a hospital is always a tough experience. People are stressed and anxious when they visit the hospital and for the health professionals, it is very difficult to respond to multiple patients at the same time. Imagine if hospital rooms could have ears to listen and respond to patients, making it easier for the patient to experience a more at-home environment inside the hospital. The cognitive environment of care powered by IBM’s Watson IoT provides that experience for patients at Thomas Jefferson University Hospital and Jefferson Health in downtown Philadelphia [95]. The system was designed based on the most common queries of patients, like changing the room temperature, changing TV channels, turning the light on or off, asking about the visiting time of their family members, etc. The hospital deployed

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JBL smart speakers, part of the system created by Hermon International, designed with a set of ears that can pick up voices from any corner of the room. Not only the patient but everybody, including nurses, doctors, and family members of the patient, can use this system. If you are a patient and someone is listening to you, then obviously it increases your mental strength, which is a very important factor in the quick recovery of a patient.

11 THE IoT HEALTHCARE MARKET: PRESENT AND FUTURE The healthcare industry is certainly poised for major growth, thanks to the enabling technologies like IoT and pervasive systems. The growth has been propelled by a range of high-tech innovations including wearable and implantable devices and the latest technologies such as Big Data analytics [96]. The next generation healthcare system will provide cost-effective and improved services while introducing a number of new healthcare service categories [97], of which the focal point will be the quality of patient care. The improved quality of service (QoS) for medical care and better disease management provided by connected healthcare will have a positive impact on patients and that will invigorate the growth of the IoT healthcare market. A high degree of automation and enhanced decision making will be the highlight of the healthcare sector in the coming years. The IoT healthcare market size, worldwide, was evaluated at $60 billion in 2014 [98] and is expected to reach $136.8 billion by 2021 [99] with a compound annual growth rate (CAGR) of 12.5%. Another study projects the CAGR of the IoT healthcare market at 30.8%, from USD 41.22 billion in 2017 to USD 158.07 billion by 2022 [100]. One of the key factors pushing this growth is the number of associated stakeholders such as hospitals, clinics, surgical centers, diagnostic laboratories, research laboratories, device suppliers, solutions (hardware, software, and networking) providers, government institutions, and the health-conscious public. The IoT healthcare market comprises software, systems, networking devices, medical and implantable devices, wearable and fitness devices, and services (Fig. 9). The advances in each area will result in cumulative growth in the IoT healthcare market. Among the global IoT healthcare market segments (refer to Table 5) viz. North America, Europe, Asia Pacific, and Rest of the World, North America holds the top position in terms of highest revenue generator and likely to hold its lead in the global market of IoT healthcare in the near future also [102]. The key factors behind North America’s substantial stake in the IoT healthcare market are the availability of advanced and sophisticated healthcare infrastructure, quality research initiatives and significant technological advancements in the areas of IoT and smart devices, medical devices, and innovative healthcare applications and use cases. But the Asia Pacific region, especially the countries like China and India, is also growing rapidly as a major market for IoT healthcare. This breakneck growth can be attributed to high economic growth, improved healthcare infrastructure, large-scale adoption of IT-enabled healthcare services, increasing affordability and popularity of various

11 The IoT healthcare market: present and future

IoT health care market

Platform

Technology

Component

Service

Application

Network management

Sensors

Hardware

Professional (individual)

Clinical care

Device management

RFID

Software

Managed (organised)

Remote monitoring

Application management

Communication technologies

Networking

Medical robotics

Supply chain and inventory

FIG. 9 Components of IoT healthcare market [101].

Table 5 Global IoT healthcare market segments [101] North America

• United States • Canada

Europe

• United • • • • •

Kingdom Germany France Italy Spain Russia

Asia Pacific

• • • •

China India Japan South Korea • Australia • Singapore • Malaysia

Rest of the World

• • • • •

Brazil Mexico Saudi Arabia UAE South Africa

wearable devices and smartphones (helps in easy accessibility of services), cheap and widely available fast data connection (e.g., 4G, Wi-Fi), etc. [102]. Many companies have tried to taste the waters of this huge business opportunity, but the majority of the market has been captured by the big players in the respective sectors (as shown in Table 6). The smaller companies are lagging behind mainly in research and development (due to funding crunches) and due to inability to come up with innovative, specialized, and practical solutions. In any case, IoT healthcare will open up many new and exciting product and service lines that will raise the market further.

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Corporation

Base country

Focus area

Services/solutions/products in healthcare

Medtronic [103]

Dublin, Ireland

Medical devices

Brain monitoring

• • • • •

BIS Quatro sensor BIS Bilateral sensor BIS Pediatric sensor BIS Extend BIS Brain monitoring OEM solution

Advanced etCO2 monitoring innovation

• Microstream microMediCO2 OEM • Microstream MicroPod External etCO2 Module Cerebral/somatic oximetry

• INVOS Cerebral/Somatic Oximetry Adult Sensors • INVOS Cerebral/Somatic Oximetry Infant-Neonatal Sensors

• INVOS Cerebral/Somatic Oximetry Solutions Pulse oximetry

• • • •

Nellcor SpO2 Forehead Sensor with OxiMax technology Nellcor Flexible SpO2 reusable sensor Nellcor Reusable SpO2 sensors with OxiMax technology Nellcor Two-Piece SpO2 sensors with OxiMax technology Capsule endoscopy

• PILLCAM SB 3 system • PILLCAM UGI capsule

CHAPTER 1 Pervasive healthcare

Table 6 The key players in the IoT healthcare market

Gastric electrical stimulation systems

• Enterra II Neurostimulator Sacral neuromodulation systems

• Interstim II Neurostimulator • Interstim Neurostimulator Diabetes healthcare

Deep brain stimulation system

• Active PC Neurostimulator • Active RC Neurostimulator • Active SC Neurostimulator Philips [104]

Amsterdam, Netherlands

Medical devices, healthcare at home

Services and solutions: Hospital telehealth

• • • •

eICU program eAcute program eConsultant program eConsultant - SNF program

Home telehealth

• eIAC program • eCAC program • eTrAC program Continued

11 The IoT healthcare market: present and future

• MiniMed Paradigm REAL-Time Revel System • iPro 2 Professional Continuous Glucose Monitoring (CGM)

47

48

Corporation

Base country

Focus area

Services/solutions/products in healthcare Enterprise information systems

• Enterprise imaging solutions • IntelliSpace Portal 10 Healthcare @ home

• • • •

Palliative care @ home Critical care @ home Respiratory care @ home Cancer care @ home

Products:

• • • • • •

Smart-hopping technology IntelliVue cableless measurement IntelliSpace alarm reporting Clinical decision support IntelliSpace event management Clinical informatics

Cisco Systems Inc. [105]

California, United States

Networking and telecommunication

Services and solutions:

IBM [106]

New York, United States

Healthcare solution and consulting service, Data analytics

Services and solutions:

• • • • • • • •

Telehealth and collaboration solutions Patient engagement solutions Clinical workflow solutions R&D and manufacturing for Life Sciences

Health system performance & optimization Population health insights & care management Individual insights & engagement IBM Watson Healthcare

CHAPTER 1 Pervasive healthcare

Table 6 The key players in the IoT healthcare market—cont’d

GE Healthcare [107]

Illinois, United States

Medical and Health devices, Healthcare solutions, Healthcare IT

Products: GE Health Cloud Enterprise imaging

• Centricity solutions for enterprise imaging • Advanced visualization powered by AW Workforce management Time and attendance Staffing and scheduling Patient classification Human resources and payroll Business analytics

Care delivery management

• • • •

Cardiovascular IT software Electronic medical record Perinatal software Perioperative software

Population health management

• Ambulatory providers and physician-led ACOs • Integrated delivery networks and hospital-led ACOs Microsoft [108]

Washington, United States

Software, computer devices

Services and solutions:

• • • • •

Patient engagement solutions Operational analytics solutions Clinical analytics solutions Care coordination solutions Cybersecurity in health solutions

Products:

• Microsoft Azure SAP [109]

Walldorf, Germany

ERP solutions

11 The IoT healthcare market: present and future

• • • • •

Services and solutions: Patient care

49

• Care delivery • Patient administration and billing Continued

50

Corporation

Base country

Focus area

Services/solutions/products in healthcare Care collaboration

• Patient engagement • Patient relationship management Healthcare analytics and research

• Healthcare analytics • Medical research insights • Connected health Qualcomm Life [110]

California, United States

Telecommunications, semiconductor devices, healthcare solutions

Products:

• 2net Platform—medical-grade remote care • Capsule—integration of medical devices and clinical data management around different hospitals.

Honeywell Life Care Solutions [111]

Wisconsin, United States

Telehealth, IT

Products:

STANLEY Healthcare [112]

United States, Singapore

Medical Alert devices, communication devices, IT solutions

Services and solutions, products:

• LifeStream clinical monitoring software • • • • •

Security and protection Environmental monitoring Patient safety Supply chain & asset management Clinical operation & workflow

CHAPTER 1 Pervasive healthcare

Table 6 The key players in the IoT healthcare market—cont’d

References

12 CONCLUSION In recent years, “staying healthy” is not just two words, but it has become a habit for a large segment of people, boosted by smart healthcare devices and the IoT. IoT has brought about revolutionary changes in the healthcare industry. It is becoming established in the healthcare sector on a remarkable scale thanks to the wide adoption of smart and connected devices in healthcare. Medical devices are increasingly being connected to each other, enabling improved patient experience and quick and timely response to emergencies. IoT brings a more expanded approach to healthcare; different applications of IoT technologies have improved our lives and transformed the ideology of staying healthy. Continuous monitoring of patient data in real time has helped the health experts to treat their patients in a more efficient manner. Connected healthcare helps doctors to manage diseases, monitor patients and improve treatment in an efficient way. Storing and analyzing patient’s previous health records has played an important role in preventive healthcare strategies. More importantly, a huge amount of demographical health information related to a mass disease outbreak and requiring solutions for that. But although connected healthcare has brought with it a lot of promises, the concept of pervasive healthcare is relatively new, and the infrastructure is still immature. There is a significant gap between what is needed and what we have, in terms of physical infrastructure, innovative applications, and utilities. For example, there is a significant mismatch between the pace and the scale at which healthcare data is generated and the capacity of the systems that are supposed to consume and use these data. Similarly, there is scope for improvement in the device management aspect, which can be leveraged for enhanced data collection and analysis. Security and privacy represent another big challenge in the successful implementation of pervasive healthcare. Hopefully, recognizing the potential benefits of connected healthcare in comparison to its downsides and risks, all the limitations and hurdles will be handled. In times ahead, it is certain that we will witness many new developments in the healthcare sector due to the continuing technological advances in these areas.

ACKNOWLEDGMENTS We would like to thank Matt Benardis, CEO, Cyrcadia Health and Marie Johnson, Ph.D., CEO, AUM Cardiovascular Inc. for giving permission to use the images of iTBra and CADence respectively.

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