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Brain computer interface advancement in neurosciences: Applications and issues
Journal Pre-proofs Review Article Brain Computer Interface advancement in Neurosciences: Applications and Issues Shiv Kumar Mudgal, Sharma Suresh K. Sharma, Itender Chaturvedi, Anil Sharma PII: DOI: Reference:
S2214-7519(20)30009-8 https://doi.org/10.1016/j.inat.2020.100694 INAT 100694
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Interdisciplinary Neurosurgery: Advanced Techni‐ ques and Case Management Interdisciplinary Neu‐ rosurgery: Advanced Techniques and Case Man‐ agement
Received Date: Revised Date: Accepted Date:
7 January 2020 15 February 2020 16 February 2020
Please cite this article as: S.K. Mudgal, S.S.K. Sharma, I. Chaturvedi, A. Sharma, Brain Computer Interface advancement in Neurosciences: Applications and Issues, Interdisciplinary Neurosurgery: Advanced Techniques and Case Management Interdisciplinary Neurosurgery: Advanced Techniques and Case Management (2020), doi: https://doi.org/10.1016/j.inat.2020.100694
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INAT 100694
Full title: Issues
Brain Computer Interface advancement in Neurosciences: Applications and
Running Title: Brain Computer Interface; Chaturvedi et. al.
Corresponding and 3rd Author: Dr. Jitender Chaturvedi Assistant Professor, Neurosurgery AIIMS, Rishikesh, India-249203 Phone number: 9900788501 Email: [email protected]
1stAuthor: Dr. Shiv Kumar Mudgal, Ph.D. Clinical Tutor, College of Nursing AIIMS, Rishikesh E-mail- [email protected] Mob. No. 9068095488
2nd Author: Prof. Sharma Suresh K Sharma, Ph.D., RN Principal, College of Nursing, AIIMS, Rishikesh E-mail- [email protected] Mob. No. 08475000293 4th Author: Dr. Anil Sharma
Assistant Professor, Neurosurgery AIIMS, Raipur, Chhattisgarh Email: [email protected] Phone: 9902629505
Brain Computer Interfaces advancement in Neurosciences: Applications and Issues Abstract: Neurosciences and Neuro-technology are continuously advancing and so are individuals, society and healthcare professionals. Brain computer Interface (BCI) is one such emerging technology in Neurosciences. In a nutshell, BCI technology provides a direct communication between brain and external device bypassing the normal neuromuscular pathways. BCI not only serves medical field & health care but also has role in various other arenas of human life like entertainment, gaming, education, self-control, marketing and so on. Associated with its advantages, BCI takes along with its pitfalls too which may fall into various categories like technological, neurological and ethical. In this review paper, authors discuss about the basic concept of BCI, brain signals and components. We also reviewed the applications of BCI in different fields and practical issues related to usability of BCI. Given the fact that it has a multidisciplinary realm, i.e. neurosciences, physicians of all specialties, nurses, engineers, hospital manager and administration, this review on the subject is written in common language. Key words: Brain Computer Interface, BCI, Neuroscience Nursing, BCI Application
Introduction Technology is one, which affects every aspect of society from invention of wheel to artificial intelligence [1]. In the health care delivery system revolutionary changes are going on due to ever increasing pace of advancement and utilization of technology to meet the changing health care needs of society [2]. These technological developments have tremendously changed the medical practice. Use of electronic health records [3], humanoid robots in health care [4], companion robots which provide special attention or assistance to old age persons or children [5], automated dispersive robots which administer the medications coupled with highly specialized artificial intelligence [6] are the few examples to quote in general; and BCI is one among the neurosciences advancement [7]. Brain computer interface with artificial intelligence is a rapidly growing new technology which provides a direct mean of communication between a silently speaking brain and the bio-monitoring devices, smart phones, earphones and other external devices [8]. Brain computer interface can be seen as a collaboration between brain and a device, which allows direct passage of electrical signals from the neurons to the external device/system such as a computer or a robotic arm. It is a powerful communication technology that does not depend on involvement of any muscle or neuromuscular pathways to complete the communication, command and thus action [9-11]. It requires direct transmission of Brain impulses to the effectors end machine bypassing the neuromuscular pathways. This basic concept can be extrapolated and clinically utilized in a paralyzed but conscious patient. For example, a paralyzed person, with his neuronal activity can make use of a cursor or control an artificial limb as electrical impulses transferred directly from the user’s brain to the mechanism, which regulate the cursor, without need of normal neuromuscular pathways right from brain to the finger [12-13]. To begin with, BCI was developed for bio medical applications, which lead to generate the assistive devices for restoration of movement and communication strength for physically disabled patients in order to rehabilitate their lost motor abilities [14]. However, the horizons of researches have been further extended to develop BCI not only for healthy persons through medical applications but also for development of non-medical applications like generations & prototypes of hand free devices [14-15]. Altogether BCI is still in experimental phase globally but has a great potential or might become clinically relevant in the near future. The involvement of these highly advanced technologies in health care delivery system particularly in
neuroscience will definitely drastically transform the medical profession. Therefore, health care providers face evergrowing challenges to integrate continuous development of technology in the medical practice [6]. These challenges demand from the doctors & all health care providers to gain knowledge about recent advancement and utilize this into practice to cope up with recent ongoing technological advancement [16]. In this review paper, authors discuss about the BCIs and its applications in neuroscience to make concerned people sensitize about this emerging sophisticated technology. As we go along, we will discuss about various types of BCI, different kinds of signals it uses to do so; and components used in this technology.
What is BCI A brain–computer interface (BCI) is a technology that receives, analyzes, and transfer the signals generated from brain into output commands in real world to accomplish a particular task. In doing so, they are unique, as they do not include the normal neuromuscular pathways of peripheral nerves and muscles to perform a function, which is the site of pathology in paralyzed patients [17].
Types of BCIs A. Event related de-synchronization (ERD-BCI) and synchronization (ERS-BCI): Based on the processing method used for input data, it can be divided into synchronous BCI and de-synchronous BCI. It has been established that changes due to any activity can reduce or stop the strength of the ongoing EEG signal. The reduction or enhancement of strength in given frequency bands can be utilized to identify these changes. These may be associated with the synchrony level of the underlying neuronal activities. The reduction and enhancement in power is known as event-related de-synchronization and event- related synchronization; respectively [18-19]. B. Exogenous BCI and Endogenous BCI: Based on which type (nature) of input signals used by BCI, it can be exogenous BCI or endogenous BCI. Exogenous BCI uses the neuronal activities generated in the brain due to external stimuli e.g. visual or auditory evoked potentials and are affected by physical characteristics of stimulus like intensity, modality, and presentation rate. While, endogenous BCIs are not affected by physical characteristics of the stimulus and are based on self-control of brain activity [8, 18-19]. C. Active BCIs, Reactive BCI and Passive BCI: Active BCI: This system generates its results from voluntary controlled activities of brain, independent from external stimulant, for managing an application e.g. BCI, which is triggered by the intentional motor imagery of a person [20].
Reactive BCI: This system uses brain signals arising as a result of reaction to external stimulant which is indirectly operated for controlling an application by the user e.g. visually evoked P300. Passive BCI: This system gets its results from unintentional affective/cognitive brain activities of brain eg. by recognizing driver’s sleepiness and thus; helps to prevent road traffic accidents.
Brain Signal Types used in BCI: Various research studies have explained different group of brain signals generated from activities in neurons that are used in BCI systems as depicted in Figure 1[8,19]. 1. Visual evoked potentials (VEPs) These are brain impulses generated in the visual cortex after picking-up visual stimulation. VEPs may be classified as per morphology and frequency of the visual stimulus or based upon area of on-screen stimuli. At first, it may be due to flash stimulus or stimulation by graphic designs like checkerboard, dot-graph and gate. Secondly, as per frequency, VEPs may be Transient VEPs (when frequency of optical stimuli is less than 6 Hz) and Steady-State VEPs (occur when optical stimulus has high frequency). Thirdly, depending on the area of on-screen stimuli; it may be whole field, half field and part field VEPs [19]. Transient VEPs may be generated by making a change in the optical field. The most commonly used changes in TVEPs may be due to: (a) flashing lights that may cause flash TVEPs (b) suddenly appearing a pattern on a diffuse background may elicit onset/offset TVEPs and (iii) changing the part or step of a pattern may generate pattern reversal TVEPs. SSVEPs are generated by the same visual stimuli but frequency is more than 6 Hz. Based on use of specific stimuli pattern modulation, SSVEP-based BCIs may be further divided as follow [18-19]: (i) time modulated VEP- BCIs (the orders of flash on different targets are orthogonal in time) (ii) frequency modulated VEP- BCIs (each target is flashed at a specific frequency) and (iii) pseudorandom code modulated VEPBCIs (the time taken for ON and OFF states of each target’s flash is determined due to a pseudorandom order).[19] 2. Slow Cortical Potentials (SCPs) An EEG-based BCI may depend on SCPs that permit anatomically specific voluntary stimulation of distinct parts of brain. SCPs are due to intra-cortical stimulation to distinct cortical layers; they develop by concurrent polarization of a large group of apical dendrites of pyramidal nerve cells, largest neuron in the human cortex, specifically in motor cortex. Cortical cell depolarization decreases excitation threshold of nerve cells, and stimulation of brain cells in areas, which control motor, or cognitive functions are enhanced. Negative SCPs associated with depolarization or enhancement of nerve cells activity, while positive SCPs are accompanied with reduction of cells activity or inhibition of cells [19, 21].
BCI
visual evoked potentials
slow cortical potentials
Evoked potentials
sensorimotor rhythms
Morphology of the optical stimuli
Positive
Steady State Evoked Potential
Beta band
Frequency of visual stimulation
Negative
Event-related Potential
Rolandic band
Field stimulation
Transient VEPs (TVEPs)
Steady-state VEPs (SSVEPs)
Figure-1 Types of brain signals used in BCI 3. Evoked potential (EP) Evoked potential or evoked response is an electrical response registered from the nervous system after the presentation of stimuli. EP may be classified as steady state evoked potential (SSEP) and event-related potential (ERP). SSEPs are elicited through a stimulus adjusted at a specific frequency and happen due to an amplification in EEG activity at the stimulation frequency. Event-related potential (ERP) is evoked due to change in stimulus. ERPs are related with a stimulus, which gives relevant information about the task [18-19]. 4. Sensorimotor Rhythms Sensorimotor rhythms contain μ-rhythm and β-rhythm, which are fluctuation of brain activities localized over sensorimotor areas in the μ band or the Rolandic band (7–13 Hz), and β band (13–30 Hz). These rhythms are movement- modulated, i.e., there is a change either when somebody executing an activity or movement performance [18-19]. Components of BCI:
Figure-2. Components of BCI in an illustration of transmission of signal between input and output with a sequence of processing steps in between. Signals are acquired by electrodes and then translated into a control signal for a machine-like neuro prosthesis or wheelchair depending on its intentional use [23]. The main aim to design a BCI is to sense and evaluate the features of signals in user’s brain, which show the intention of the user and send these characters of signals to the external device that execute to fulfill the intention of user. [22] To accomplish this aim, a BCI based system contains 4 sequent components (Figure 2) [23-24]: (1) signal acquisition, (2) processing, (3) translation, and (4) device output or feedback.
1. Signal Acquisition: It is first part of BCI system, which sense and measures the signals of brain. This component is mainly accountable for receiving & registering the signals generated by neuronal activity and transferring these signals to the next component of BCI (preprocessing part) for signals improvement and electrical noise attenuation [8, 11-13]. There are three common methods used for signal acquisition:
Invasive: In this type of BCI, very small electrodes are directly implanted into the brain i.e. cortex for assess the neuronal activities exa. Invasive intracranial electrodes [25-26].
Semi-Invasive: In this type of BCI, electrodes are implanted either in epidural or in arachnoids space exa. Electrocorticogram (ECoG) [25].
Non-Invasive: In this type of BCI, electrodes are placed on the scalp. In non-invasive system, EEG (electroencephalography) uses most commonly, although MEG (magneto encephalography), PET (positron emission tomography), fMRI (functional magnetic resonance imaging) and fNIRS (functional near-infrared spectroscopy) have been started to use recently [11, 26].
Table-1: Summary of signal acquisition method
Types
Example
Signal type
Portability
Spatial
Temporal
resolution
resolution
Intra-cortical
Electrical
Portable
Very high
High
ECoG
Electrical
Portable
High
High
EEG
Electrical
Portable
Low
Mediate
MEG
Magnetic
Non-portable
Mediate
Mediate
fMRI
Metabolic
Non-portable
High
Low
fNIRS
Metabolic
Portable
Mediate
Low
Invasive Semi-Invasive
Non-Invasive
2. Feature Extraction: The first step of signal-processing part of BCI is feature extraction. This is an activity of examining the digitally appear signals to different characters of relevant signal (like, characteristic of signal coupled to the intention of user) from irrelevant information and presenting signal in a acceptable manner to translate them for output commands. This component develops the selective features for the enhanced signal, reducing the data size applicable to the next component (classification) [8, 13]. 3. Translation It is second step of signal processing in this the extracted characters of signal are transferred into translation algorithm, then characters convert into relevant instructions necessary for the external device to accomplish the intention (e.g. instructions which complete the intention of the user) [13,27]. 4. Device Output The instructions received from the translation algorithm, guide and control the output device. It helps accomplishing the intention of user like selection of alphabets, control of mouse, robotic arm movement, to operate a wheelchair, to
move a paralyzed limb using a neuroprosthesis and so on. At present, computer is the most commonly used output device used for communication [13, 27-29].
Application of BCI Recently, BCIs have been used in health care, education, environmental control, entertainment & games, pain management, safety and security, social interaction and Space applications. As BCI is a multidisciplinary field, which includes its research, connection from computer science, engineering, applied mathematics, psychology, neuroscience and rehabilitation. As BCI is one of the most recent advancement in field of neuroscience [8, 11, 26]. Brain Computer Interfaces in Healthcare: The utilization of BCI in health care has immense potential and is highly needed in all aspects like prevention, early diagnosis and treatment of disease; and restoration with rehabilitation [30].
Prevention:
Road traffic accidents are the most cause for head injury and related mortality. It can be prevented by using BCI [31]. The utilization neuro-feedback of BCI to maintain attention and motion sickness during a prolonged work like driving can prevent accidents [31]. A review has been carried out to assess the behavior of drivers and showed that fatigue and distraction are two most common reasons for inattention of drivers, which are associated factors for majority of road traffic accidents [32]. Numerous measures were analyzed among drivers for detection of fatigue, sleep deprivation and workload [33-34] to predict concentration and stress of drivers by evaluating EEG signals and manage the speed of vehicle through brain signal concentration values [35]. Another study explained the application of BCI to increase the attention level of drivers when they feel drowsiness and delayed by 1.7 times when compared with the group to whom stimulus was not applied [35-36]. while one study carried out to detect the feasibility to assess the emergency situation like unexpected appearance of a vehicle or person by using the EEG signals of driver and concluded that detection model can detect the emergency situation within one second (which was less than the reaction time of drivers) and estimated accuracy was near 70% [37].
Early Detection:
BCI technology can be used for early detection of abnormal brain structure and functions that contributed to predicting and identifying the pathological state. Examples being like space occupying lesions (e.g. brain cancer, encephalitis), abnormal neuronal discharge (seizure) and disorders related to sleep. Brain tumor and feasibility of BCI technology by using EEG, which could be cheap, easy, low risk and early detection tool as a secondary alternative or addendum to CT scan or MRI [38-39]. Another study suggests an automated EEG analysis system which identified abnormalities detect in EEG due to tumor and seizure with accuracy of 98%, 93% and 87% for normal, epilepsy and brain tumor respectively [40]. Researchers have proposed seizure control measures by using closed-loop brain computer interface which showed high rate of seizure diagnosis (92-99% during wake-sleep
states), low rate of false diagnosis (1.2-2.5%) [41]. Early diagnosis of seizure disorder and its control by using artificial neural network were proposed in other studies [42-43]. Disorders related to sleep such as narcolepsy, idiopathic rapid eye movement and sleep behavior disorder (it has been found to be a strong risk factor for Parkinson’s disease) can be detected through BCI technology using EEG signals more accurately than the current diagnostic methods [44-46]. BCI technology is useful to diagnose dyslexia, [47] human gait cycle, [48] attention-deficit hyperactivity disorder [49] and improve the symptoms of ADHD when a training programme which used BCI was implemented [50]. Rehabilitation: One of the important aspects of the care after neurological disabilities like injury to head or spinal cord, CVA, amyotrophic lateral sclerosis, is to regain the damage motor function or ability to communicate; and enhance quality of life through rehabilitation [21]. Neuro-rehabilitation could be enhanced by using BCI technology for the people who are suffering with motor, communication and control issue due to neurological damage [51]. The main aim of BCI application can be divided into two areas: Communication and Restoration. Communication means the BCI’s ability to make the patient able, not only to communicate by using devices such as word processors, speech synthesizers and use of email functions, but also control the devices like wheelchair and prosthetic devices [51]. Lastly restoration means the modalities based on BCI technology for regaining of lost motor function for the patients with neurological diseases like SCI, stoke [18, 52]. A study mentioned that parts of the brain involved in brain stroke could be detected and brain can still control a prosthetic limb if BCI technology is used [53] and impaired motor functions could be rehabilitated through BCI based neuro-feedback [54]. The advantages and efficacy of BCI technology, as it uses neuroplasticity with combination of traditional physiotherapy, in patients after stroke in rehabilitation program were suggested [55]. It has been discussed in studies that activities of daily living can be completed by mobile robots through EEG based BCI for helping the patient with locked-in-syndrome [56-57]. Numerous studies suggested that neuroprosthetic devices, which use motor imagery based BCI technology, could be useful to restoration of normal functioning level for those patients who could not regain prior levels of upper limb movement [58-59]. Different reality approaches like real, virtual and augmented have been proposed which are based on BCI system for rehabilitation program. Real approach for rehabilitation, which helps the patients after stroke through adjusting patient’s thinking pattern, which are similar to the recorded signals and retain unaffected parts of the brain to gain control. This approach utilizes signals of brain produced from healthy persons accompanying with the decoded kinematic standards [60]. Virtual reality, which uses computer technology for creation of stimulated experience [61], is another modality in rehabilitation. A pilot study project suggests that virtual reality based BCI is feasible and effective in stroke rehabilitation [62]. A clinical study’s preliminary results showed that the use of virtual reality and BCI with functional electrical stimulator have the good satisfaction, rapid adaptation with therapy and fast progress in rehabilitation among the users [63]. Augmented reality, the third approach utilized to exploit the experience of reality, resulting in new rehabilitative approach. For example, augmented mirror box system is used for development
of Mirror Box Therapy. This therapy utilizes signals produced from brain by symmetrical movements, which integrated affected and unaffected limbs [64]. The results of a review, which assess the effectiveness of augmented reality in shoulder rehabilitation showed that augmented reality, have more advantages than the traditional programme [65]. BCI and Smart Environment: A cognitive controller system known as BCI based Smart Living Environmental Auto –Adjusted Control System (BSLEACS) has been suggested which can detects mental state of user and adjust the nearby components correspondingly and BCI technology can be integrated with universal plug and play (UPnP) home networking for smart home utilization [66]. BCI could be utilized in providing safety, luxury and physiological control on ADLs at home, offices and transportation. It has been proposed that BCI exploits in enhancing working environment conditions by assessing employee’s cognitive state, effect of workload and working time on mental fatigue [66-67]. BCI and Self-Control: The applicability of BCI in learning to self-control studied and a study has been carried out to evaluate the feasibility of fMRI to regulate the emotion whereas, another study proposed the application of hybrid BCI (rtf MRI-EEG BCI) to manage to symptoms or feeling of depression and other neuropsychiatric problems via training sessions. Furthermore, it has been examined the EEG based emotional intelligence to control the sport competition related stress [2, 8]. BCI and Marketing: The advantages of BCI application in commercial, social and political advertisement have been discussed as through use BCI they were able to detect the impact of TV advertisement on memorization and therefore, this technology provides a different tool for analysis the impact of advertisement [68]. BCI and Security: Currently, most of the security systems are based on knowledge like password, object or biometric identification but they have their own issues or drawbacks like unsafe password, shoulder suffering and duplication of biometric. The use of brain signals in cognitive biometric for a proof of identification have been provided answers for those drawbacks. Moreover, these systems could be utilized to send warning message whenever a authentic person is under external pressure [69-70]. BCI and Entertainment & games: BCI contributes the application in the fields of entertainment and gaming. Various games like flying helicopters are made to fly to any point in either a 2 D or 3-D virtual world. The Brain Arena, a BCI based video football game where players can score a goal by imagine left- or right-hand movements. A study explained Brain ball game that intends to decrease the level of stress. In this game players can only move the ball when they feel relax and a user
who is calmer or relax usually win the game. Therefore, they would try to learn to control or decrease their stress level [8]. Pitfalls and Setback in application of BCI Brain computer interfaces technology attracts the researchers in different fields because this technology is useful in both medical as well as non-medical field like smart environment, games, safety etc as discussed earlier. On the other hand, usability of BCI technology is associated with various issues and we summarized these issues in to three categories such as neuro-psycho-physiological, technical, ethical Figure-3 [8, 11, 24, 68, 70]. a. Neuro-psycho-physiological Issues: Neurological issues include problems related to the anatomy of brain like genetic complexity and diversity of the structure of human brain. One study also suggested that the volume of gray matter in sensory-motor part of brain is related to success of BCI. Moreover, BCI system also depends on the brain function or activity, for example, one study suggested that approximately 15-30% of people are genetically unable to produce sufficient signals to control or operate a BCI system. Psychological issues include attention, memory, fatigue, stress and emotions, which are, depend on individual personality. Moreover, BCI, also affected by user’s basic characteristics like age, gender, and life-style [8, 11, 24]. b. Technological Issues: Technological issues are challenges related to various components of the BCI system. For example, Event related potential are produced by external stimulation and target-specific. If ERPs depend on visual stimulation so cannot be utilized for rehabilitation of patients with ALS who have problem with visual processing. In this situation, we are supposed to use auditory-based ERP, if auditory functions remain normal. Another example regarding spatial resolution, EEG gives poor resolution because of non-invasive recording when compared with f MRI. Therefore, it is a big issue to select a standard method for acquisition and processing of brain signals. Another challenge that is faced by BCI user’s is BCI illiteracy which means user’s limitation to control BCI system and need a training [8,11, 24]. c. Ethical Issues: These concerns are related to physical and mental safety of users, for example invasive procedure could be risk factors for bleeding, infection, and other surgical complications. Moreover, these are also associated with psychological problems such as, altered behaviors that may lead to threats to user’s emotion, personality and memory. Threats to the alteration of user’s cognitive, emotional and physical state raise a serious ethical issue. These issues are also concerned with the privacy and confidentiality of BCI user’s data; acceptance by the community and financial burden. Another important issue is to obtain consent from the user who have difficulty in communications [8,11,70].
Structural divercity of human brain
Neuro-Psychophysiological
Mood variation
Resting state unstability
Risk related to invasive procedure
Portability Signal Acquisition Cost effectiveness Pitfalls
BCI illiteracy Difficult and tedious set-up Technological Not standarization of cortical waves Quality of signal
Signal processing
- Associated risks
-privacy and confidentiality of information
Ethical
Standarization of neurotechnology
Socioeconomic issues
Figure-3 Pitfalls and Setbacks related to BCI
Data driven factors
Problem of source localization
Conclusion: Brain computer interface is an innovative technology that uses brain signals to control an external device to accomplish a task bypassing normal neuromuscular pathway. This makes a disabled person to communicate with environment. BCI technology is a recent advancement in neurosciences and attracted the researchers from various other disciplines too e.g. entertainment & games, security and marketing. Brain Computer Interface technology may still be experimental, but it definitely has a great potential and might become clinically relevant for day to day medical practice in near future. Given the multidisciplinary realm it covers i.e. neurosciences, physicians of all specialties, nurses, engineers, hospital manager and administration, it is surely going to change the way we provide neurosurgical services to our patient and help us achieve the neurosciences laboratory advances we yearn. Currently BCI technology may appear to some as a standstill in laboratory, however, the way we are going to rehabilitate traumatic brain injury patients in future will be completely different from what we are doing today. In this review paper, authors attempted to communicate a summary on BCI and its application with related issues like technical, neurological as well as ethical by reviewing the pertinent literature on BCI technology, discussing the fundamental components of BCI, it’s applicability in myriad fields and types of signals it uses to do so. In particular, this paper explores the neuro-scientific basis of BCI especially rehabilitative utilization. This review provides an opportunity for various health care providers like doctors, nurses, bio-medical engineers and hospital administrators to get sensitize, start learning and enhance one’s knowledge about this futuristic neurotechnological advancement.
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Brain–computer interface (BCI) is a technology that receives, analyzes, and transfer the signals generated from brain into output commands in real world to accomplish a particular task. It provides a direct communication between brain and external devices bypassing the normal neuromuscular pathways. BCI not only serves medical field & health care but also has role in various other arenas of human life like entertainment, gaming, education, self-control, marketing and so on. Given the fact that it has a multidisciplinary realm, i.e. neurosciences, physicians of all specialties, nurses, engineers, hospital manager and administration, this review on the subject is written in common language. Altogether BCI is still in experimental phase globally but has a great potential or might become clinically relevant in the near future.
S2214-7519(20)30009-8 https://doi.org/10.1016/j.inat.2020.100694 INAT 100694
To appear in:
Interdisciplinary Neurosurgery: Advanced Techni‐ ques and Case Management Interdisciplinary Neu‐ rosurgery: Advanced Techniques and Case Man‐ agement
Received Date: Revised Date: Accepted Date:
7 January 2020 15 February 2020 16 February 2020
Please cite this article as: S.K. Mudgal, S.S.K. Sharma, I. Chaturvedi, A. Sharma, Brain Computer Interface advancement in Neurosciences: Applications and Issues, Interdisciplinary Neurosurgery: Advanced Techniques and Case Management Interdisciplinary Neurosurgery: Advanced Techniques and Case Management (2020), doi: https://doi.org/10.1016/j.inat.2020.100694
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© 2020 Published by Elsevier B.V.
INAT 100694
Full title: Issues
Brain Computer Interface advancement in Neurosciences: Applications and
Running Title: Brain Computer Interface; Chaturvedi et. al.
Corresponding and 3rd Author: Dr. Jitender Chaturvedi Assistant Professor, Neurosurgery AIIMS, Rishikesh, India-249203 Phone number: 9900788501 Email: [email protected]
1stAuthor: Dr. Shiv Kumar Mudgal, Ph.D. Clinical Tutor, College of Nursing AIIMS, Rishikesh E-mail- [email protected] Mob. No. 9068095488
2nd Author: Prof. Sharma Suresh K Sharma, Ph.D., RN Principal, College of Nursing, AIIMS, Rishikesh E-mail- [email protected] Mob. No. 08475000293 4th Author: Dr. Anil Sharma
Assistant Professor, Neurosurgery AIIMS, Raipur, Chhattisgarh Email: [email protected] Phone: 9902629505
Brain Computer Interfaces advancement in Neurosciences: Applications and Issues Abstract: Neurosciences and Neuro-technology are continuously advancing and so are individuals, society and healthcare professionals. Brain computer Interface (BCI) is one such emerging technology in Neurosciences. In a nutshell, BCI technology provides a direct communication between brain and external device bypassing the normal neuromuscular pathways. BCI not only serves medical field & health care but also has role in various other arenas of human life like entertainment, gaming, education, self-control, marketing and so on. Associated with its advantages, BCI takes along with its pitfalls too which may fall into various categories like technological, neurological and ethical. In this review paper, authors discuss about the basic concept of BCI, brain signals and components. We also reviewed the applications of BCI in different fields and practical issues related to usability of BCI. Given the fact that it has a multidisciplinary realm, i.e. neurosciences, physicians of all specialties, nurses, engineers, hospital manager and administration, this review on the subject is written in common language. Key words: Brain Computer Interface, BCI, Neuroscience Nursing, BCI Application
Introduction Technology is one, which affects every aspect of society from invention of wheel to artificial intelligence [1]. In the health care delivery system revolutionary changes are going on due to ever increasing pace of advancement and utilization of technology to meet the changing health care needs of society [2]. These technological developments have tremendously changed the medical practice. Use of electronic health records [3], humanoid robots in health care [4], companion robots which provide special attention or assistance to old age persons or children [5], automated dispersive robots which administer the medications coupled with highly specialized artificial intelligence [6] are the few examples to quote in general; and BCI is one among the neurosciences advancement [7]. Brain computer interface with artificial intelligence is a rapidly growing new technology which provides a direct mean of communication between a silently speaking brain and the bio-monitoring devices, smart phones, earphones and other external devices [8]. Brain computer interface can be seen as a collaboration between brain and a device, which allows direct passage of electrical signals from the neurons to the external device/system such as a computer or a robotic arm. It is a powerful communication technology that does not depend on involvement of any muscle or neuromuscular pathways to complete the communication, command and thus action [9-11]. It requires direct transmission of Brain impulses to the effectors end machine bypassing the neuromuscular pathways. This basic concept can be extrapolated and clinically utilized in a paralyzed but conscious patient. For example, a paralyzed person, with his neuronal activity can make use of a cursor or control an artificial limb as electrical impulses transferred directly from the user’s brain to the mechanism, which regulate the cursor, without need of normal neuromuscular pathways right from brain to the finger [12-13]. To begin with, BCI was developed for bio medical applications, which lead to generate the assistive devices for restoration of movement and communication strength for physically disabled patients in order to rehabilitate their lost motor abilities [14]. However, the horizons of researches have been further extended to develop BCI not only for healthy persons through medical applications but also for development of non-medical applications like generations & prototypes of hand free devices [14-15]. Altogether BCI is still in experimental phase globally but has a great potential or might become clinically relevant in the near future. The involvement of these highly advanced technologies in health care delivery system particularly in
neuroscience will definitely drastically transform the medical profession. Therefore, health care providers face evergrowing challenges to integrate continuous development of technology in the medical practice [6]. These challenges demand from the doctors & all health care providers to gain knowledge about recent advancement and utilize this into practice to cope up with recent ongoing technological advancement [16]. In this review paper, authors discuss about the BCIs and its applications in neuroscience to make concerned people sensitize about this emerging sophisticated technology. As we go along, we will discuss about various types of BCI, different kinds of signals it uses to do so; and components used in this technology.
What is BCI A brain–computer interface (BCI) is a technology that receives, analyzes, and transfer the signals generated from brain into output commands in real world to accomplish a particular task. In doing so, they are unique, as they do not include the normal neuromuscular pathways of peripheral nerves and muscles to perform a function, which is the site of pathology in paralyzed patients [17].
Types of BCIs A. Event related de-synchronization (ERD-BCI) and synchronization (ERS-BCI): Based on the processing method used for input data, it can be divided into synchronous BCI and de-synchronous BCI. It has been established that changes due to any activity can reduce or stop the strength of the ongoing EEG signal. The reduction or enhancement of strength in given frequency bands can be utilized to identify these changes. These may be associated with the synchrony level of the underlying neuronal activities. The reduction and enhancement in power is known as event-related de-synchronization and event- related synchronization; respectively [18-19]. B. Exogenous BCI and Endogenous BCI: Based on which type (nature) of input signals used by BCI, it can be exogenous BCI or endogenous BCI. Exogenous BCI uses the neuronal activities generated in the brain due to external stimuli e.g. visual or auditory evoked potentials and are affected by physical characteristics of stimulus like intensity, modality, and presentation rate. While, endogenous BCIs are not affected by physical characteristics of the stimulus and are based on self-control of brain activity [8, 18-19]. C. Active BCIs, Reactive BCI and Passive BCI: Active BCI: This system generates its results from voluntary controlled activities of brain, independent from external stimulant, for managing an application e.g. BCI, which is triggered by the intentional motor imagery of a person [20].
Reactive BCI: This system uses brain signals arising as a result of reaction to external stimulant which is indirectly operated for controlling an application by the user e.g. visually evoked P300. Passive BCI: This system gets its results from unintentional affective/cognitive brain activities of brain eg. by recognizing driver’s sleepiness and thus; helps to prevent road traffic accidents.
Brain Signal Types used in BCI: Various research studies have explained different group of brain signals generated from activities in neurons that are used in BCI systems as depicted in Figure 1[8,19]. 1. Visual evoked potentials (VEPs) These are brain impulses generated in the visual cortex after picking-up visual stimulation. VEPs may be classified as per morphology and frequency of the visual stimulus or based upon area of on-screen stimuli. At first, it may be due to flash stimulus or stimulation by graphic designs like checkerboard, dot-graph and gate. Secondly, as per frequency, VEPs may be Transient VEPs (when frequency of optical stimuli is less than 6 Hz) and Steady-State VEPs (occur when optical stimulus has high frequency). Thirdly, depending on the area of on-screen stimuli; it may be whole field, half field and part field VEPs [19]. Transient VEPs may be generated by making a change in the optical field. The most commonly used changes in TVEPs may be due to: (a) flashing lights that may cause flash TVEPs (b) suddenly appearing a pattern on a diffuse background may elicit onset/offset TVEPs and (iii) changing the part or step of a pattern may generate pattern reversal TVEPs. SSVEPs are generated by the same visual stimuli but frequency is more than 6 Hz. Based on use of specific stimuli pattern modulation, SSVEP-based BCIs may be further divided as follow [18-19]: (i) time modulated VEP- BCIs (the orders of flash on different targets are orthogonal in time) (ii) frequency modulated VEP- BCIs (each target is flashed at a specific frequency) and (iii) pseudorandom code modulated VEPBCIs (the time taken for ON and OFF states of each target’s flash is determined due to a pseudorandom order).[19] 2. Slow Cortical Potentials (SCPs) An EEG-based BCI may depend on SCPs that permit anatomically specific voluntary stimulation of distinct parts of brain. SCPs are due to intra-cortical stimulation to distinct cortical layers; they develop by concurrent polarization of a large group of apical dendrites of pyramidal nerve cells, largest neuron in the human cortex, specifically in motor cortex. Cortical cell depolarization decreases excitation threshold of nerve cells, and stimulation of brain cells in areas, which control motor, or cognitive functions are enhanced. Negative SCPs associated with depolarization or enhancement of nerve cells activity, while positive SCPs are accompanied with reduction of cells activity or inhibition of cells [19, 21].
BCI
visual evoked potentials
slow cortical potentials
Evoked potentials
sensorimotor rhythms
Morphology of the optical stimuli
Positive
Steady State Evoked Potential
Beta band
Frequency of visual stimulation
Negative
Event-related Potential
Rolandic band
Field stimulation
Transient VEPs (TVEPs)
Steady-state VEPs (SSVEPs)
Figure-1 Types of brain signals used in BCI 3. Evoked potential (EP) Evoked potential or evoked response is an electrical response registered from the nervous system after the presentation of stimuli. EP may be classified as steady state evoked potential (SSEP) and event-related potential (ERP). SSEPs are elicited through a stimulus adjusted at a specific frequency and happen due to an amplification in EEG activity at the stimulation frequency. Event-related potential (ERP) is evoked due to change in stimulus. ERPs are related with a stimulus, which gives relevant information about the task [18-19]. 4. Sensorimotor Rhythms Sensorimotor rhythms contain μ-rhythm and β-rhythm, which are fluctuation of brain activities localized over sensorimotor areas in the μ band or the Rolandic band (7–13 Hz), and β band (13–30 Hz). These rhythms are movement- modulated, i.e., there is a change either when somebody executing an activity or movement performance [18-19]. Components of BCI:
Figure-2. Components of BCI in an illustration of transmission of signal between input and output with a sequence of processing steps in between. Signals are acquired by electrodes and then translated into a control signal for a machine-like neuro prosthesis or wheelchair depending on its intentional use [23]. The main aim to design a BCI is to sense and evaluate the features of signals in user’s brain, which show the intention of the user and send these characters of signals to the external device that execute to fulfill the intention of user. [22] To accomplish this aim, a BCI based system contains 4 sequent components (Figure 2) [23-24]: (1) signal acquisition, (2) processing, (3) translation, and (4) device output or feedback.
1. Signal Acquisition: It is first part of BCI system, which sense and measures the signals of brain. This component is mainly accountable for receiving & registering the signals generated by neuronal activity and transferring these signals to the next component of BCI (preprocessing part) for signals improvement and electrical noise attenuation [8, 11-13]. There are three common methods used for signal acquisition:
Invasive: In this type of BCI, very small electrodes are directly implanted into the brain i.e. cortex for assess the neuronal activities exa. Invasive intracranial electrodes [25-26].
Semi-Invasive: In this type of BCI, electrodes are implanted either in epidural or in arachnoids space exa. Electrocorticogram (ECoG) [25].
Non-Invasive: In this type of BCI, electrodes are placed on the scalp. In non-invasive system, EEG (electroencephalography) uses most commonly, although MEG (magneto encephalography), PET (positron emission tomography), fMRI (functional magnetic resonance imaging) and fNIRS (functional near-infrared spectroscopy) have been started to use recently [11, 26].
Table-1: Summary of signal acquisition method
Types
Example
Signal type
Portability
Spatial
Temporal
resolution
resolution
Intra-cortical
Electrical
Portable
Very high
High
ECoG
Electrical
Portable
High
High
EEG
Electrical
Portable
Low
Mediate
MEG
Magnetic
Non-portable
Mediate
Mediate
fMRI
Metabolic
Non-portable
High
Low
fNIRS
Metabolic
Portable
Mediate
Low
Invasive Semi-Invasive
Non-Invasive
2. Feature Extraction: The first step of signal-processing part of BCI is feature extraction. This is an activity of examining the digitally appear signals to different characters of relevant signal (like, characteristic of signal coupled to the intention of user) from irrelevant information and presenting signal in a acceptable manner to translate them for output commands. This component develops the selective features for the enhanced signal, reducing the data size applicable to the next component (classification) [8, 13]. 3. Translation It is second step of signal processing in this the extracted characters of signal are transferred into translation algorithm, then characters convert into relevant instructions necessary for the external device to accomplish the intention (e.g. instructions which complete the intention of the user) [13,27]. 4. Device Output The instructions received from the translation algorithm, guide and control the output device. It helps accomplishing the intention of user like selection of alphabets, control of mouse, robotic arm movement, to operate a wheelchair, to
move a paralyzed limb using a neuroprosthesis and so on. At present, computer is the most commonly used output device used for communication [13, 27-29].
Application of BCI Recently, BCIs have been used in health care, education, environmental control, entertainment & games, pain management, safety and security, social interaction and Space applications. As BCI is a multidisciplinary field, which includes its research, connection from computer science, engineering, applied mathematics, psychology, neuroscience and rehabilitation. As BCI is one of the most recent advancement in field of neuroscience [8, 11, 26]. Brain Computer Interfaces in Healthcare: The utilization of BCI in health care has immense potential and is highly needed in all aspects like prevention, early diagnosis and treatment of disease; and restoration with rehabilitation [30].
Prevention:
Road traffic accidents are the most cause for head injury and related mortality. It can be prevented by using BCI [31]. The utilization neuro-feedback of BCI to maintain attention and motion sickness during a prolonged work like driving can prevent accidents [31]. A review has been carried out to assess the behavior of drivers and showed that fatigue and distraction are two most common reasons for inattention of drivers, which are associated factors for majority of road traffic accidents [32]. Numerous measures were analyzed among drivers for detection of fatigue, sleep deprivation and workload [33-34] to predict concentration and stress of drivers by evaluating EEG signals and manage the speed of vehicle through brain signal concentration values [35]. Another study explained the application of BCI to increase the attention level of drivers when they feel drowsiness and delayed by 1.7 times when compared with the group to whom stimulus was not applied [35-36]. while one study carried out to detect the feasibility to assess the emergency situation like unexpected appearance of a vehicle or person by using the EEG signals of driver and concluded that detection model can detect the emergency situation within one second (which was less than the reaction time of drivers) and estimated accuracy was near 70% [37].
Early Detection:
BCI technology can be used for early detection of abnormal brain structure and functions that contributed to predicting and identifying the pathological state. Examples being like space occupying lesions (e.g. brain cancer, encephalitis), abnormal neuronal discharge (seizure) and disorders related to sleep. Brain tumor and feasibility of BCI technology by using EEG, which could be cheap, easy, low risk and early detection tool as a secondary alternative or addendum to CT scan or MRI [38-39]. Another study suggests an automated EEG analysis system which identified abnormalities detect in EEG due to tumor and seizure with accuracy of 98%, 93% and 87% for normal, epilepsy and brain tumor respectively [40]. Researchers have proposed seizure control measures by using closed-loop brain computer interface which showed high rate of seizure diagnosis (92-99% during wake-sleep
states), low rate of false diagnosis (1.2-2.5%) [41]. Early diagnosis of seizure disorder and its control by using artificial neural network were proposed in other studies [42-43]. Disorders related to sleep such as narcolepsy, idiopathic rapid eye movement and sleep behavior disorder (it has been found to be a strong risk factor for Parkinson’s disease) can be detected through BCI technology using EEG signals more accurately than the current diagnostic methods [44-46]. BCI technology is useful to diagnose dyslexia, [47] human gait cycle, [48] attention-deficit hyperactivity disorder [49] and improve the symptoms of ADHD when a training programme which used BCI was implemented [50]. Rehabilitation: One of the important aspects of the care after neurological disabilities like injury to head or spinal cord, CVA, amyotrophic lateral sclerosis, is to regain the damage motor function or ability to communicate; and enhance quality of life through rehabilitation [21]. Neuro-rehabilitation could be enhanced by using BCI technology for the people who are suffering with motor, communication and control issue due to neurological damage [51]. The main aim of BCI application can be divided into two areas: Communication and Restoration. Communication means the BCI’s ability to make the patient able, not only to communicate by using devices such as word processors, speech synthesizers and use of email functions, but also control the devices like wheelchair and prosthetic devices [51]. Lastly restoration means the modalities based on BCI technology for regaining of lost motor function for the patients with neurological diseases like SCI, stoke [18, 52]. A study mentioned that parts of the brain involved in brain stroke could be detected and brain can still control a prosthetic limb if BCI technology is used [53] and impaired motor functions could be rehabilitated through BCI based neuro-feedback [54]. The advantages and efficacy of BCI technology, as it uses neuroplasticity with combination of traditional physiotherapy, in patients after stroke in rehabilitation program were suggested [55]. It has been discussed in studies that activities of daily living can be completed by mobile robots through EEG based BCI for helping the patient with locked-in-syndrome [56-57]. Numerous studies suggested that neuroprosthetic devices, which use motor imagery based BCI technology, could be useful to restoration of normal functioning level for those patients who could not regain prior levels of upper limb movement [58-59]. Different reality approaches like real, virtual and augmented have been proposed which are based on BCI system for rehabilitation program. Real approach for rehabilitation, which helps the patients after stroke through adjusting patient’s thinking pattern, which are similar to the recorded signals and retain unaffected parts of the brain to gain control. This approach utilizes signals of brain produced from healthy persons accompanying with the decoded kinematic standards [60]. Virtual reality, which uses computer technology for creation of stimulated experience [61], is another modality in rehabilitation. A pilot study project suggests that virtual reality based BCI is feasible and effective in stroke rehabilitation [62]. A clinical study’s preliminary results showed that the use of virtual reality and BCI with functional electrical stimulator have the good satisfaction, rapid adaptation with therapy and fast progress in rehabilitation among the users [63]. Augmented reality, the third approach utilized to exploit the experience of reality, resulting in new rehabilitative approach. For example, augmented mirror box system is used for development
of Mirror Box Therapy. This therapy utilizes signals produced from brain by symmetrical movements, which integrated affected and unaffected limbs [64]. The results of a review, which assess the effectiveness of augmented reality in shoulder rehabilitation showed that augmented reality, have more advantages than the traditional programme [65]. BCI and Smart Environment: A cognitive controller system known as BCI based Smart Living Environmental Auto –Adjusted Control System (BSLEACS) has been suggested which can detects mental state of user and adjust the nearby components correspondingly and BCI technology can be integrated with universal plug and play (UPnP) home networking for smart home utilization [66]. BCI could be utilized in providing safety, luxury and physiological control on ADLs at home, offices and transportation. It has been proposed that BCI exploits in enhancing working environment conditions by assessing employee’s cognitive state, effect of workload and working time on mental fatigue [66-67]. BCI and Self-Control: The applicability of BCI in learning to self-control studied and a study has been carried out to evaluate the feasibility of fMRI to regulate the emotion whereas, another study proposed the application of hybrid BCI (rtf MRI-EEG BCI) to manage to symptoms or feeling of depression and other neuropsychiatric problems via training sessions. Furthermore, it has been examined the EEG based emotional intelligence to control the sport competition related stress [2, 8]. BCI and Marketing: The advantages of BCI application in commercial, social and political advertisement have been discussed as through use BCI they were able to detect the impact of TV advertisement on memorization and therefore, this technology provides a different tool for analysis the impact of advertisement [68]. BCI and Security: Currently, most of the security systems are based on knowledge like password, object or biometric identification but they have their own issues or drawbacks like unsafe password, shoulder suffering and duplication of biometric. The use of brain signals in cognitive biometric for a proof of identification have been provided answers for those drawbacks. Moreover, these systems could be utilized to send warning message whenever a authentic person is under external pressure [69-70]. BCI and Entertainment & games: BCI contributes the application in the fields of entertainment and gaming. Various games like flying helicopters are made to fly to any point in either a 2 D or 3-D virtual world. The Brain Arena, a BCI based video football game where players can score a goal by imagine left- or right-hand movements. A study explained Brain ball game that intends to decrease the level of stress. In this game players can only move the ball when they feel relax and a user
who is calmer or relax usually win the game. Therefore, they would try to learn to control or decrease their stress level [8]. Pitfalls and Setback in application of BCI Brain computer interfaces technology attracts the researchers in different fields because this technology is useful in both medical as well as non-medical field like smart environment, games, safety etc as discussed earlier. On the other hand, usability of BCI technology is associated with various issues and we summarized these issues in to three categories such as neuro-psycho-physiological, technical, ethical Figure-3 [8, 11, 24, 68, 70]. a. Neuro-psycho-physiological Issues: Neurological issues include problems related to the anatomy of brain like genetic complexity and diversity of the structure of human brain. One study also suggested that the volume of gray matter in sensory-motor part of brain is related to success of BCI. Moreover, BCI system also depends on the brain function or activity, for example, one study suggested that approximately 15-30% of people are genetically unable to produce sufficient signals to control or operate a BCI system. Psychological issues include attention, memory, fatigue, stress and emotions, which are, depend on individual personality. Moreover, BCI, also affected by user’s basic characteristics like age, gender, and life-style [8, 11, 24]. b. Technological Issues: Technological issues are challenges related to various components of the BCI system. For example, Event related potential are produced by external stimulation and target-specific. If ERPs depend on visual stimulation so cannot be utilized for rehabilitation of patients with ALS who have problem with visual processing. In this situation, we are supposed to use auditory-based ERP, if auditory functions remain normal. Another example regarding spatial resolution, EEG gives poor resolution because of non-invasive recording when compared with f MRI. Therefore, it is a big issue to select a standard method for acquisition and processing of brain signals. Another challenge that is faced by BCI user’s is BCI illiteracy which means user’s limitation to control BCI system and need a training [8,11, 24]. c. Ethical Issues: These concerns are related to physical and mental safety of users, for example invasive procedure could be risk factors for bleeding, infection, and other surgical complications. Moreover, these are also associated with psychological problems such as, altered behaviors that may lead to threats to user’s emotion, personality and memory. Threats to the alteration of user’s cognitive, emotional and physical state raise a serious ethical issue. These issues are also concerned with the privacy and confidentiality of BCI user’s data; acceptance by the community and financial burden. Another important issue is to obtain consent from the user who have difficulty in communications [8,11,70].
Structural divercity of human brain
Neuro-Psychophysiological
Mood variation
Resting state unstability
Risk related to invasive procedure
Portability Signal Acquisition Cost effectiveness Pitfalls
BCI illiteracy Difficult and tedious set-up Technological Not standarization of cortical waves Quality of signal
Signal processing
- Associated risks
-privacy and confidentiality of information
Ethical
Standarization of neurotechnology
Socioeconomic issues
Figure-3 Pitfalls and Setbacks related to BCI
Data driven factors
Problem of source localization
Conclusion: Brain computer interface is an innovative technology that uses brain signals to control an external device to accomplish a task bypassing normal neuromuscular pathway. This makes a disabled person to communicate with environment. BCI technology is a recent advancement in neurosciences and attracted the researchers from various other disciplines too e.g. entertainment & games, security and marketing. Brain Computer Interface technology may still be experimental, but it definitely has a great potential and might become clinically relevant for day to day medical practice in near future. Given the multidisciplinary realm it covers i.e. neurosciences, physicians of all specialties, nurses, engineers, hospital manager and administration, it is surely going to change the way we provide neurosurgical services to our patient and help us achieve the neurosciences laboratory advances we yearn. Currently BCI technology may appear to some as a standstill in laboratory, however, the way we are going to rehabilitate traumatic brain injury patients in future will be completely different from what we are doing today. In this review paper, authors attempted to communicate a summary on BCI and its application with related issues like technical, neurological as well as ethical by reviewing the pertinent literature on BCI technology, discussing the fundamental components of BCI, it’s applicability in myriad fields and types of signals it uses to do so. In particular, this paper explores the neuro-scientific basis of BCI especially rehabilitative utilization. This review provides an opportunity for various health care providers like doctors, nurses, bio-medical engineers and hospital administrators to get sensitize, start learning and enhance one’s knowledge about this futuristic neurotechnological advancement.
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Brain–computer interface (BCI) is a technology that receives, analyzes, and transfer the signals generated from brain into output commands in real world to accomplish a particular task. It provides a direct communication between brain and external devices bypassing the normal neuromuscular pathways. BCI not only serves medical field & health care but also has role in various other arenas of human life like entertainment, gaming, education, self-control, marketing and so on. Given the fact that it has a multidisciplinary realm, i.e. neurosciences, physicians of all specialties, nurses, engineers, hospital manager and administration, this review on the subject is written in common language. Altogether BCI is still in experimental phase globally but has a great potential or might become clinically relevant in the near future.