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MEMS for in vivo sensing
3 MEMS for in vivo sensing S. ARAVAMUDHAN, North Carolina A&T State University, USA
Abstract: The development of in vivo sensors for continuous monitoring of human health conditions is an area of sustained scientific and technological interest. This chapter highlights the important trends and challenges for microelectromechanical systems (MEMS) and microsystem-based in vivo sensors. The interest in applying MEMS technology for biological applications has grown rapidly because of some of its unique features such as better performance, high sensitivity, fast responsiveness, temporal control, size, cost, and comparable feature sizes. Finally, issues relating to short-term (acute) and long-term (chronic) implantation, along with future prospects for the application of MEMS in implantable biosensors, are discussed. Key words: bioMEMS, implantable, biosensors, biocompatibility, smart microsystems.
3.1
Introduction
Medicine and biology are among the most promising and the most challenging fields of application for microelectromechanical systems (MEMS) and microsystem technologies. MEMS is a technology developed from integrated circuit manufacturing to create miniature sensors and actuators. Medical devices based on MEMS technology (called as bioMEMS) are currently being developed for a wide variety of in vivo and point-of-care applications. The interest in MEMS for medical applications has grown rapidly, with increased opportunities in areas such as implantable biosensors, pacemakers, immunoisolation capsules, and drug-delivery microchips. The goal of this chapter is to highlight the important concepts, opportunities, challenges, and current trends in implantable MEMS sensors. The fundamental objective of in vivo MEMS sensors is to (a) facilitate clinical diagnosis of human health conditions and/or (b) provide therapeutic modalities via closed-loop control. When MEMS sensors are combined with integrated processors and telemetry circuits, a number of physical, chemical, or biological variables within the human body can be monitored and can thereby allow for evaluation of an individual’s medical condition. With an ultimate goal, utilize the same device to administer an ‘ondemand’ therapeutic drug via a remote trigger (Santini et al., 1999). The MEMS devices were first used in medical applications in the early 1970s with the advent of the silicon-micromachined disposable blood 81 © Woodhead Publishing Limited, 2012
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pressure sensors (Blazer et al., 1971). Over the last decades, there has been an exponential growth in number of MEMS devices for biomedical applications (Kovacs, 1998). This exponential growth is primarily due to the fact that MEMS technology provides device miniaturization (Kovacs, 1998; Wilkinson, 2001; Ziaie et al., 2004; Schurr, 2007), better performance or functionality (Lee, 1999), efficient transduction processes, higher reaction rate, lower reagent consumption, lower weight, lower unit cost per device, and higher reliability (Kovacs, 1998). Furthermore, the developments in these devices have been driven by the inherent desire to better mimic human physiology and to improve the quality-of-life. The overarching vision for MEMS sensors and devices are to address the major global healthcare challenges such as an ever-aging population, patient-centered care, and affordable costs. As stated earlier, one of the most prominent medical applications for bioMEMS is the field of in vivo sensors and ‘on-demand’ drug-eluting implants. For example, in vivo biosensors have the ability to provide metabolite(s) level(s) continuously regardless of the patient’s physiological state (rest, sleep, exercise, etc.) and without any external intervention (Vaddiraju et al., 2010). It is quite obvious that miniaturization (using MEMS technology) is a key desirable requirement for in vivo devices. This is especially true for implants in very small organs or those that are inserted using minimally invasive surgery, where the maximum allowable size is restricted by the working channel diameter. An important example in this regard is in diabetes management, which at present relies on test strip data (using blood drawn from finger pricking). This procedure is not only invasive and painful but also is incapable of reflecting the overall trends and patterns associated with patient’s daily habits (Reach and Wilson, 1992). This led to large-scale research efforts focused on developing in vivo biosensors for continuous monitoring of various biologically relevant metabolites (Koschwanez and Reichert, 2007). The other classes of sensors that have been intensively researched include sensors for nerve stimulation capable of alleviating acute pain (Schneider and Stieglitz, 2004), sensors for detecting electric signals in brain (Hu and Wilson, 1997a, 1997b), and sensors for monitoring bioanalytes (O’Neill, 1994), intraocular pressure (IOP) monitoring (Ha et al., 2011), and drug-delivery microchips for controlled delivery at the site of pain and stress (Ryu et al., 2007). In general, in vivo devices are often complex systems and consist of multiple components such as sensors, power sources, control units, and modules for wireless communication, potentially resulting in bulky overall device architecture if appropriate packaging technologies are not used. Other packaging requirement is often the material used for construction. In other words, the materials that make intimate contact to biological matter under test have to be biocompatible to avoid unintentional effects on cells and tissues. In the
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case of in vivo sensors, the use of nonbiocompatible materials could potentially interfere with the biological subcomponents that in turn could affect the sensor stability and performance (Velten et al., 2005). For example, the sensors must be packaged and sterilized, and the resulting device must be biocompatible with the host system into which it is implanted. According to Madou, ‘Biocompatibility is the single most complex issue facing in vivo sensor development and it needs addressing up front in the sensor design’ (Madou, 2002). The reliability of in vivo systems are often undermined by a host of other factors such as biofouling (Wisniewski et al., 2001; Gifford et al., 2006) and foreign body response (Wisniewski et al., 2000), sensor drifts, and lack of temporal resolution (Kerner et al., 1993). The scope of this chapter is to discuss the current trends in MEMS in vivo sensors and the above-mentioned challenges in detail. This chapter aims to highlight the current trends of in vivo MEMS sensors with special emphasis on MEMS biosensors. In the following sections, various subsystems and few relevant case studies of in vivo sensors are discussed (Section 3.2). The chapter concludes with an outlook of the challenges and opportunities for MEMS-based in vivo sensors (Section 3.3).
3.2
Overview of MEMS in vivo devices and sensors
An in vivo biomedical system is any device that is intended to function inside the body for some period of time. A lot of work has been done in the application of MEMS technology for this purpose to adapt various types of sensors for in vivo applications (Amy and Langer, 2004). The aim of this section is to give a global overview of which MEMS- and microsystembased sensors are being used and how they are clinically applied for in vivo applications. The goal of short-term sensing of biological variables such as pH, analytes, and pressure in blood, tissue, and body fluids has largely been achieved, but stable sensors for long-term applications continue to elude researchers because of various reasons (Gough and Armour, 1995; Abel and von Woedtke, 2002). Long-term in vivo sensing is a critical component of an ideal closed-loop drug-delivery or monitoring system, but the issues of in vivo biocompatibility and biofouling are still being addressed in order to achieve in vivo sensing for longer periods. It is also essential that the degree of biocompatibility and minimal tissue response must be greater for sensor applications compared to other types of implants. All material systems irrespective of their biocompatibility produce some degree of tissue response. For example, implants can create partial isolation from the body. This typically does not impede the functions that are essentially mechanical in nature such as in case of drug-delivery systems, orthopedic, or tissue engineering applications. However, implant isolation can lead to greatly reduced sensitivity and increased response time in case of sensor
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applications. As the intimate interaction of sensor and analyte is inherent to the operation of in vivo sensors, the biocompatibility challenge in case of in vivo sensors remains the biggest stumbling block. In summary, efforts are currently under way to commercialize MEMS biosensors in vivo, especially for the less problematic short-term sensing applications, while challenges in long-term applications are being actively addressed. MEMS biosensors have incorporated various sensing strategies including electrochemical (Gough, 1988; Ward et al., 2002), mechanical (Piso and Veiga-Crespo, 2011), magnetic (Huang et al., 2009), and optical (McNichols and Cote, 2000) along with combinations of the above methods. For example, combined optical and electrochemical sensors have been developed to monitor local pH in brain tissue and in blood (Grant et al., 2000). Furthermore, multiparametric sensors have been reported that combines electrochemical and fiber-optic technology for continuous in vivo measurement of pH, carbon dioxide partial pressure, oxygen partial pressure, and oxygen saturation early in human pregnancy (Jauniaux et al., 1999). These illustrations indicate an important feature of MEMS that is their ability to operate in multiple modalities so that a broader utility can be leveraged.
3.2.1 Subsystems for in vivo sensors The various subsystems of a MEMS in vivo sensor are (a) the fabrication methodology, (b) the material used, (c) the packaging technology, (d) the power requirement, and (e) the communication system. Fabrication methodology: The fabrication process involves various bulk and surface micromachining techniques such as thin layer deposition, sacrificial layer etching, photolithographic patterning, and etching. Processes compatible with complementary metal oxide semiconductor (CMOS) allow integration with electronic circuitry. In some instances, ‘nontraditional’ fabrication processes from disciplines such as chemistry or biology are used, for example, in electrochemical sensors or surface coatings. Detailed discussion on these techniques can be found elsewhere in this book. Materials: The choice of materials for in vivo applications is limited due to stringent requirements of biostability and biocompatibility. Biostability means that the material must withstand the immune system of the body and biocompatibility means that the material must not cause any unwanted reactions in the body. A standard list of biocompatible and biostable materials does not exist, since the mechanisms involved depend on various complex details such as material processing, shape, finish, posttreatment, and impurities. While it is beyond the scope of this chapter to fully discuss material
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properties and issues, we briefly discuss some material compatibility challenges later in this chapter. Packaging technology: The human body is a very hostile and complex environment for foreign bodies that enter it, due to an active immune system. Therefore, the delicate parts of the sensor often need to be protected by a hermetic package. The electrical connections need to be routed by means of hermetic feedthroughs. Furthermore, the electrical conductors and interconnections outside of the hermetic package need to be also biostable. The readers are referred elsewhere for detailed discussions on hermetic protection, electrical feedthrough, interconnect, and conductors (Velten et al., 2005). In addition to package, coatings are used to improve the interface of the implant with the body organs (Ashammakhi and Tormala, 2004). The criteria for an excellent coating are their edge covering, peel resistance, and integrity of the coating film. In general, polymers are the most widely used coating material because of their comparable Young’s’ modulus and interfacial properties. Surface topology modifications can also provide the desired response of the body (Desai et al., 2000). Power requirements: In cases of autonomous chronic implants, power consumption is an important design constraint. Much of the development efforts have been invested in implantable batteries with sufficient longevity to address both continuous operation and small form-factor requirement. An interesting approach in this aspect is using electrostatic or piezoelectric conversion of mechanical vibrations. A capacitance or piezoelectric change due to external vibrations can cause current generation (Wang et al., 2010). In other approaches, implantable biofuel cells are also being investigated. Communication systems: It is essential that communication link with the in vivo sensor allows to either receive data concerning the sensor status or patient condition or to send data to the sensor to (re)program it. Recent advances in radio frequency (RF) systems have enabled detection from deep within the lossy medium of the body. Entirely passive circuits that are wirelessly connected to detect measurable changes have been implemented. An optical telemetry link to transmit data to an external controller is also a viable option.
3.2.2 Case studies of in vivo sensors As described earlier, the fundamental objective of in vivo MEMS sensors is to (a) facilitate clinical diagnosis of human health conditions and/or (b) provide therapeutic modalities via closed-loop control (Receveur et al., 2007). In addition to the previously stated challenges that need to be considered, the important design parameters for most in vivo sensors are power consumption, size, sensitivity, specificity, accuracy, and stability. We will begin
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our discussion on examples of in vivo sensors starting with the most common type of MEMS sensor – the pressure sensor. MEMS pressure sensors are mostly made by following the surface micromachining process. In this architecture, a suspended thin mechanical membrane is created by etching a sacrificial layer. The membrane deflection caused by pressure variations is transduced with the help of piezoresistors on the high-strain areas of the membrane and appropriate electronic circuitry. By using a CMOScompatible micromachining processes, readout circuitry can be integrated close to the sensor. MEMS pressure sensors have enormous potential for in vivo applications. A capacitance-based pressure sensor can be fabricated with the membrane deforming according to a pressure difference, causing a change in capacitance between the membrane and an electrode on the surface. For example, (Ziaie and Najafi, 2001) demonstrated a capacitancebased pressure sensor tested in vitro on a silastic tube made to mimic a pliable blood vessel. This system can be implanted in small mammals to measure blood pressure for hypertension and cardiovascular physiology. Pressure sensors Cardiovascular pressure sensors: Blood pressure at various anatomical positions contains clinically relevant information. Pressure proximal and distal to an occlusion can be measured to quantify its severity in terms of flow reserve (Pijls et al., 1993). Blood pressure can also be measured before and after a balloon catheter operation (Receveur et al., 2007). MEMS pressure sensors on catheters offer advantages over fluid-filled catheters with external transducers. They do not suffer from catheter whip, limited frequency response, and resonance. Due to their small size, these sensors can reach small places while yielding pressure readings comparable to reference sensors (Receveur et al., 2007). The continuous monitoring of pressure for cardiovascular applications using wireless implantable microsystems offers additional opportunities for better therapies and increased quality-of-life for a number of conditions such as heart failure, coronary artery disease, aneurysm, hypertension, and arrhythmias. For example, a passive wireless MEMS pressure sensor developed by CardioMEMS can monitor endovascularly repaired abdominal aortic aneurysms (Allen, 2005). This sensor consists of flexible plates bearing inductor windings (along with associated distributed capacitances) bound to a hermetically sealed reference cavity. The inductor windings serve two purposes: (a) forming a resonant electrical circuit with the capacitor and (b) magnetically coupling with an external loop. A change in the pressure surrounding the sensor will change the position of the plates, thereby changing the capacitance and resonant frequency of the sensor. The change in resonant frequency causes a change in the response of the external loop, which in turn is monitored by external
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electronics (Allen, 2005). In an another example, an implantable hemodynamic monitoring system containing a power source, integrated circuitry, a piezoelectric activity sensor, and a radiofrequency transmission coil hermetically sealed in a titanium can was developed to monitor chronic heart failure (Magalski et al., 2002). IOP sensors: Long-term, continuous IOP measurements offer a new perspective for patients suffering from glaucoma. Glaucoma is the loss of vision due to the damage of the optic nerve for which elevated IOP is an important risk factor. Chen et al. developed an implantable parylene-based wireless pressure sensor for continuous IOP monitoring in glaucoma patients (Chen and Tai, 2008). The sensor consists of electrical LC tank resonant circuit formed by an integrated capacitor and an inductor coil to facilitate passive wireless sensing using an external interrogating coil connected to a readout unit. Two surface-micromachined sensor designs incorporating variable capacitor and variable capacitor/inductor resonant circuits were implemented to realize the pressure-sensitive components. The sensor was monolithically microfabricated by exploiting parylene as a biocompatible structural material in a suitable form factor for minimally invasive intraocular implantation. Intracranial pressure sensors: For patients suffering from head injury or diseases such as chronic hydrocephalus or brain tumors, an increase in intracranial pressure is observed. In these cases, continuous measurement using a wireless implanted system offers the advantage of increased mobility, reduces the mortality risk, and enables continuous intracranial pressure monitoring to other adverse symptoms (Chapman et al., 1990). Using surface-micromachined polysilicon membranes for capacitive absolute pressure detection and monolithic integrated circuitry, an interdisciplinary consortium developed an implantable telemetric endosystem (Zacheja et al., 1995). Pressure sensors for other in vivo applications: A host of other medical conditions can also be monitored using MEMS pressure sensors. For example, urodynamic investigations to diagnose urinary problems involve interventions in the bladder and simultaneous measurements. Totally in vivo pressure monitoring systems would enable measurements under close to normal life circumstances for the patients. In other examples, a small pill-shaped biotelemeter is used for monitoring the health of a fetus during and after in utero fetal surgery. Finally, a miniaturized MEMS cell covered by a semipermeable diaphragm implanted microinvasively into the anterior chamber of the eye has been proposed as a glucose sensor (Receveur et al., 2007). Glucose sensors Diabetes mellitus is a worldwide public health problem. This metabolic disorder results from insulin deficiency and hyperglycemia and is reflected
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by blood glucose concentrations higher or lower than the normal range of 80–120 mg/dL (4.4–6.6 mM). The disease is one of the leading causes of death and disability in the world. Diabetic individuals are at a greater risk heart disease, stroke, high blood pressure, blindness, kidney failure, neurological disorders, and other health-related complications without diligent monitoring blood glucose concentrations (Turner and Pickup, 1985). To monitor glucose level using electrochemical principles, glucose oxidase (GOx) is immobilized on a microfabricated electrode. GOx is an enzyme that facilitates the oxidation of glucose to produce hydrogen peroxide. Micromachined electrodes have the advantages of fast response time, high reliability, and low cost due to mass production. However, the output current is very low because of its small size and difficulty in immobilizing GOx on the electrode surface. Therefore, the main technological challenges of these types of sensors are in the charge transfer mechanism and the GOx immobilization. Various groups have demonstrated electroenzymatic glucose sensors designed for implantation in subcutaneous tissue for continuous glucose monitoring (Johnson et al., 1992). At present, six minimally invasive blood glucose monitoring systems have been approved by the Food and Drug Administration (FDA) (Morais et al., 2010). Nevertheless, the longest in vivo functional lifetime of a marketed system is 7 days, and frequent calibration is required with handheld glucose meters. Despite outstanding advances in the in vitro functionality of such sensors, a reliable long-term and continuous glucose monitoring in vivo has not as yet been achieved due to the gradual loss of sensor functionality following implantation. Numerous investigators have suggested that glucose diffusion is negatively influenced by nonspecific protein adsorption from the tissue fluid to the sensor surface (Morais et al., 2010). Other examples of in vivo sensors The measurement of blood flow is relevant for the diagnosis of cardiovascular disease, for monitoring restenosis in stents, or for optimizing settings of pacemakers (Receveur et al., 2007). Steeves et al. (2007) designed a smart wireless sensing unit for noninvasive early stenosis detection in heart bypass grafts. Magnetic sensors are used to facilitate navigation during clinical procedures. One such system has a three-dimensional (3D) magnetic sensor embedded on a catheter. Strain sensors are used in dental care and orthopedics to monitor the status of tissue/bone implants. Melik et al. (2008) developed a passive, on-chip, RF-MEMS strain sensors that rely on the resonance frequency shift with mechanical deformation for the assessment of bone fractures. In summary, information from multiple sensors located on the tip of a catheter will ultimately help the doctor to improve diagnosis, monitor the procedure, and assess the effectiveness of therapy during procedures
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such as minimal invasive transvenous cardiological or neurological surgeries (Goosen et al., 2000).
3.2.3 Integrating biosensors and drug delivery The need for ‘on-demand’ individualized therapy has been a long held vision but largely unattainable goal. ‘On-demand’ drug-delivery systems will integrate biosensors capable of monitoring the levels of physiological parameters of a patient and, in response, trigger the release of drugs on a need basis, to customize drug administration and minimize harmful side effects. In other words, for effective individualized therapy, sensing of a biomarker indicative of a disease and subsequent delivery of the drug is essential. An ideal microfabricated in vivo drug-delivery system should integrate sensors and storage and release components into a self-regulating ‘smart’ device that could perform with minimal intervention (Tsai and Kulinsky, 2009). This being a challenging task can only be accomplished if each component is developed individually and optimized before full integration. Tsai et al. demonstrated a prototype drug-delivery device consisting of two parts: a molded PDMS drug/biosensor reservoir and a silicon substrate containing a drug-release valve. In this model system, Tsai et al. showed the integration of a biosensor for glucose employing glucose oxidase immobilized on a hydrogel contained within microfabricated vials of a device, which, in addition, contains a drugdelivery reservoir large enough (microliter volumes) to dispense therapeutic levels of protein biopharmaceuticals, such as insulin. The sensing element was stored in the microvial to be protected from continuous exposure to harsh environments (e.g., the human body), and, when desired, the lid of the valve can be opened, and the microsensor exposed to the stream of the marker/analyte. Once sampling and/or detection of the target marker were accomplished, the lid was closed again. The valve can then be reopened when an additional measurement is needed. In the drug-delivery application, the valve was open when a dose was required, and closed again after the desired amount was deployed (Tsai and Kulinsky, 2009).
3.3
Challenges and possible solutions to in vivo sensing methodology
Understanding the interaction between the implanted MEMS sensors and the local cellular environment and assessment of the immune response are critical for optimizing the performance of MEMS in vivo. In this section, we review the current understanding of the biocompatibility and foreign body response as applicable to MEMS in vivo sensors and examine the current strategies to improve the biocompatibility of MEMS.
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MEMS for biomedical applications Table 3.1 ISO 10993-1 and FDA biological response tests In vivo tests for tissue compatibility Initial evaluation steps Cytotoxicity Sensitization Irritation Intracutaneous reactivity Systematic toxicity (acute toxicity) Subchronic toxicity (subacute toxicity) Genotoxicity Implantation Hemocompatibility Supplementary evaluation steps Chronic toxicity Carcinogenicity Reproductive and developmental toxicity Biodegradation Source: Morais et al. (2010).
Table 3.2 Materials, sensors, and devices relevant to in vivo assessment of tissue compatibility In vivo assessment of tissue compatibility Material(s) of manufacture Intended additives, process contaminants, and residues Leachable substances Degradation products Other components and their interactions in the final product Properties and characteristics of the final product Source: Morais et al. (2010).
3.3.1 MEMS biocompatibility Biocompatibility is defined by The Williams Dictionary of Biomaterials as ‘the ability of a material to perform with an appropriate host response in a specific application’ (Williams, 1999). However, the biocompatibility requirements vary considerably depending on the device function and design. The performance of sensors (glucose, pH, etc.), for example, is limited by biofouling and isolation of the sensor surface. However, neural electrodes must remain in intimate contact with the neurons that they are stimulating or recording. In general, for all in vivo measurements, the implanted sensor perturbs the environment and initiates a response. This can translate into approximately 50% loss of sensitivity in vivo as compared to in vitro values (Stockl et al., 2000). Recent works have made it clear that biocompatibility does not mean that an implant is inert. Rather biocompatibility has been
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defined operationally as: minimal perturbation of the in vivo environment and similarly the in vivo environment does not adversely affect the sensor performance (Von Recum and Jacobi, 1999). Any device intended for long-term in vivo applications has to fulfill rigorous biocompatibility and biostability requirements (Anderson and Langone, 1999). First, it should not induce toxicity in the surrounding tissues and should not damage the local tissue due to induced mechanical stresses. Second, the drug-eluting capabilities of the MEMS device should not be compromised by the surrounding tissue. Specifically, the implant must tolerate long-term exposure to the physiological environment, as well as resist the impact of the surrounding tissue on its function (biofouling) (Ratner, 2004). The ISO 10-993 standards outline minimum tests of material characterization, toxicity, and biodegradation that may be augmented depending on actual device/sensor usage (Table 3.1). The general principles that may apply to the biological evaluation of materials, sensors, and devices are described in Table 3.2 (Morais et al., 2010).
3.3.2 Biofouling and surface modification The ultimate utility of many implantable MEMS sensors may be limited by another device–biological environment challenge – namely, biofouling. The adsorption of biomolecules (peptides and proteins) followed by cells frequently leads to device fouling and failure. Large-scale research efforts are being devoted toward developing methods to substantially reduce the phenomenon and produce devices that do not promote biofouling, yet retain their biocompatibility. This effort often takes the form of surface chemical modification of the device. Several recent reviews cover general issues in bioadhesion and protein adsorption (Blawas and Reichert, 1998). Chemical modification to reduce biofouling falls into one of two general methods. The first method uses surface-immobilized polymers that reduce the adsorption of biological materials. The second method relies on the self-assembly process to passivate the MEMS device surface (Ratner, 2004).
3.3.3 Foreign body response A foreign body response based on nonspecific protein adsorption, immunity, and inflammatory cells occurs under normal physiological conditions in order to protect the body from the foreign object, in this case the in vivo sensor. The acute inflammatory response starts immediately after the sensor is implanted. During the initial acute response, fluid carrying plasma proteins and inflammatory cells migrates to the site of the sensor. The proteins are adsorbed initially and then phagocytic cells (neutrophils, monocytes, and
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macrophages) surround the biosensor and attempt to destroy it. However, because a biosensor is relatively large, only ‘frustrated phagocytosis’ occurs, seen as the release of reactive oxygen species and enzymes intended to degrade the implant (Wilson and Gifford, 2005). The exact timing, action, and intensity of the process are dependent on the nature of the foreign body, which relates to size, shape, and physical and chemical properties. The acute response lasts normally about 3 days after which a chronic inflammatory response may set in or a modified version of the healing process will begin. Ultimately, a fibrotic capsule is formed, which is the hallmark of the foreign body response (Wilson and Gifford, 2005). This fibrous wall confines the implant and consequently prevents it from interacting with the surrounding tissue. To overcome the limited in vivo functionality and longevity of implantable sensors, some important approaches include biocompatible material coatings, steroidal and nonsteroidal anti-inflammatory drugs, and angiogenic drugs (Morais et al., 2010).
3.3.4 Sensor performance criteria The challenge for in vivo biosensors is to provide adequate performance to distinguish among other entities in a manner that leads to enhanced understanding of the biological function (Wilson and Gifford, 2005). That requires sensor specificity with appropriate spatial and temporal resolution within acceptable sensitivity and limits of detection (LOD) for each analyte. It is also necessary to achieve optimum balance among the figures of merit for a specific application. In addition, the biosensor must be reasonably stable, which is longer than a few hours, with days or weeks preferable. The minimum useful stability is defined by the duration of the experiment, which for in vivo applications may be hours or days in a hostile environment.
3.4
Regulatory dimensions
Medical products, of which sensors are a subset, are subject to many regulatory controls. The FDA and European Community determine whether a product is fit for sale in the United States and Europe, respectively. It is critical to understand the fundamentals of current regulatory procedures because of the complexity of obtaining product approval. Additionally, relevant procedures and guidance have been evolving extensively in the last several years. Historically, bioMEMS have had design cycles between 5 and 15 years long. Lengthy sets of clinical trials can be avoided if MEMS sensors can be applied to existing medical tools and do not claim to alter the performance. The regulatory body classifies medical devices based on the same criteria, which includes device category, placement on or in the
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body, and duration of contact with the body. An implantable biosensor is classified as an implantable device that will contact body tissue or bone for more than 30 days (United States Pharmacopeial Convention). Based on the classification of the device, the appropriate tests need to be determined from the test selection matrix. Once identified from the matrix, the corresponding test standards should be identified and followed as outlined. The readers are referred elsewhere for the summary of recommended tests (Koschwanez and Reichert, 2007). These guidelines are in accordance with the device categories and suggested biological testing set forth by the FDA.
3.5
Conclusions and future trends
This chapter has provided a general and broad overview of MEMS sensors for in vivo applications. MEMS have many characteristics that make them appealing for medical and biological applications. However, a host of biological challenges need to be addressed for reliable in vivo performance. Furthermore, in vivo sensors have to interface to the biological environment in order to function, and since the body is an active and complex system trying to control this interface, achieving the requirements on the different aspects is often challenging especially for chronic (long-term) applications. However, the clinical advantages are driving the efforts aimed at overcoming these challenges. Apart from biological challenges, MEMS design criteria in terms of power consumption, size, sensitivity, specificity, accuracy, and stability also need to be considered. Other challenges include long development times, packaging, and biocompatibility and biostability. In summary, the growing interest in combining MEMS devices with biology, and in using microsystem technology for ‘on-demand’ drugdelivery systems, may ultimately lead the way to integrated MEMS-based systems that could augment or replace entire biological systems in the human body.
3.6
References
Abel, P. U. and von Woedtke, T. 2002. Biosensors for in vivo glucose measurement: can we cross the experimental stage. Biosens Bioelectron, 17, 1059–1070. Allen, M. 2005. Micromachined endovascularly-implantable wireless aneurysm pressure sensors: From concept to clinic. The 13th International Conference on Solid-State Sensors, Actuators and Microsystems, Seoul, Korea, June 5–9, 2005. Amy, C. and Langer, R. 2004. A BioMEMS review: MEMS technology for physiologically integrated devices. Proc IEEE, 92, 6–21. Anderson, J. M. and Langone, J. J. 1999. Issues and perspectives on the biocompatibility and immunotoxicity evaluation of implanted controlled release systems. J Control Release, 57, 107–113.
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Ashammakhi, N. and Tormala, P. 2004. From past to present and future is today: From inert to multifunctional biomaterials. J Craniofac Surg, 15, 897. Blawas, A. S. and Reichert, W. M. 1998. Protein patterning. Biomaterials, 19, 595–609. Blazer, E., Koh, W. and Yon, E. 1971. A miniature digital pressure transducer, Proc 24th Ann Conf Eng Med Biol, 211. Chapman, P. H., Cosman, E. R. and Arnold, M. A. 1990. The relationship between ventricular fluid pressure and body position in normal subjects and subjects with shunts: A telemetric study. Neurosurgery, 26, 181–189. Chen, P.-J. and Tai, Y.-C. 2008. Microfabricated implantable parylene-based wireless passive intraocular pressure sensors. J Microelectromech Systems, 17, 1342–1351. Desai, T. A., Hansford, D. J., Leoni, L., Essenpreis, M. and Ferrari, M. 2000. Nanoporous anti-fouling silicon membranes for biosensor applications. Biosens Bioelectron, 15, 453–462. Gifford, R., Kehoe, J. J., Barnes, S. L., Kornilayev, B. A., Alterman, M. A. and Wilson, G. S. 2006. Protein interactions with subcutaneously implanted biosensors. Biomaterials, 27, 2587–2598. Goosen, J. F. L., French, P. J. and Sarro, P. M. 2000. Pressure, flow and oxygen saturation sensors on one chip for use in catheters. Proc. IEEE 13th Ann. Int. Conf. Micro Electro Mechanical Systems, Miyazaki, Japan, Jan 23–27, 537–540. Gough, D. A. 1988. Issues related to in vitro operation of potentially implantable enzyme electrode glucose sensors. Horm Metab Res Suppl, 20, 30–33. Gough, D. A. and Armour, J. C. 1995. Development of the implantable glucose sensor. What are the prospects and why is it taking so long? Diabetes, 44, 1005–1009. Grant, S. A., Bettencourt, K., Krulevitch, P., Hamilton, J. and Glass, R. 2000. Development of fiber optic and electrochemical pH sensors to monitor brain tissue. Crit Rev Biomed Eng, 28, 159–163. Ha, D., De Vries, W. N., John, S. W., Irazoqui, P. P. and Chappell, W. J. 2011. Polymerbased miniature flexible capacitive pressure sensor for intraocular pressure (IOP) monitoring inside a mouse eye. Biomed Microdevices, 14(1), 207–215. Hu, Y. and Wilson, G. S. 1997a. Rapid changes in local extracellular rat brain glucose observed with an in vivo glucose sensor. J Neurochem, 68, 1745–1752. Hu, Y. and Wilson, G. S. 1997b. A temporary local energy pool coupled to neuronal activity: fluctuations of extracellular lactate levels in rat brain monitored with rapid-response enzyme-based sensor. J Neurochem, 69, 1484–1490. Huang, S., Yang, H., Lakshmanan, R. S., Johnson, M. L., Wan, J., Chen, I. H., Wikle, H. C., 3rd, Petrenko, V. A., Barbaree, J. M. and Chin, B. A. 2009. Sequential detection of Salmonella typhimurium and Bacillus anthracis spores using magnetoelastic biosensors. Biosens Bioelectron, 24, 1730–1736. Jauniaux, E., Watson, A., Ozturk, O., Quick, D. and Burton, G. 1999. In vivo measurement of intrauterine gases and acid–base values early in human pregnancy. Hum Reprod, 14, 2901–2914. Johnson, K. W., Mastrototaro, J. J., Howey, D. C., Brunelle, R. L., Burden-Brady, P. L., Bryan, N. A., Andrew, C. C., Rowe, H. M., Allen, D. J., Noffke, B. W., et al. 1992. In vivo evaluation of an electroenzymatic glucose sensor implanted in subcutaneous tissue. Biosens Bioelectron, 7, 709–714. Kerner, W., Kiwit, M., Linke, B., Keck, F. S., Zier, H. and Pfeiffer, E. F. 1993. The function of a hydrogen peroxide-detecting electroenzymatic glucose electrode is markedly impaired in human sub-cutaneous tissue and plasma. Biosens Bioelectron, 8, 473–482.
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Koschwanez, H. E. and Reichert, W. M. 2007. In vitro, in vivo and post explantation testing of glucose-detecting biosensors: current methods and recommendations. Biomaterials, 28, 3687–3703. Kovacs, G. T. A. 1998. Micromachined Transducers Sourcebook, Boston, MA, WCB. Lee, A. P. 1999. Micro-Electro-Mechanical Systems (MEMS) – 1999, New York, NY, American Society of Mechanical Engineers. Madou, M. J. 2002. Fundamentals of Microfabrication: The Science of Miniaturization, Boca Raton, FL, CRC Press. Magalski, A., Adamson, P., Gadler, F., Boehm, M., Steinhaus, D., Reynolds, D., Vlach, K., Linde, C., Cremers, B., Sparks, B. and Bennett, T. 2002. Continuous ambulatory right heart pressure measurements with an implantable hemodynamic monitor: A multicenter, 12-month follow-up study of patients with chronic heart failure. J Card Fail, 8, 63–70. Mcnichols, R. J. and Cote, G. L. 2000. Optical glucose sensing in biological fluids: an overview. J Biomed Opt, 5, 5–16. Melik, R., Perkgoz, N. K. and Demir, H. V. 2008. Bio-implantable passive on-chip RF-MEMS strain sensing resonators for orthopaedic applications. J Micromech Microeng, 18, 115017. Morais, J. M., Papadimitrakopoulos, F. and Burgess, D. J. 2010. Biomaterials/tissue interactions: Possible solutions to overcome foreign body response. AAPS J, 12, 188–196. O’Neill, R. D. 1994. Microvoltammetric techniques and sensors for monitoring neurochemical dynamics in vivo. A review. Analyst, 119, 767–779. Pijls, N. H., Van Son, J. A., Kirkeeide, R. L., De Bruyne, B. and Gould, K. L. 1993. Experimental basis of determining maximum coronary, myocardial, and collateral blood flow by pressure measurements for assessing functional stenosis severity before and after percutaneous transluminal coronary angioplasty. Circulation, 87, 1354–1367. Piso, D. and Veiga-Crespo, P. 2011. Application specific integrated circuits in implantable sensors for monitoring intraocular pressure. Arch Soc Esp Oftalmol, 86, 311–313. Ratner, B. D. 2004. Biomaterials Science: An Introduction to Materials in Medicine, Amsterdam, Boston, Elsevier Academic Press. Reach, G. and Wilson, G. S. 1992. Can continuous glucose monitoring be used for the treatment of diabetes. Anal Chem, 64, 381A–386A. Receveur, R. A. R., Lindemans, F. W. and De Rooij, N. F. 2007. Microsystem technologies for implantable applications. J Micromech Microeng, 17, R50–R80. Ryu, W., Huang, Z., Prinz, F. B., Goodman, S. B. and Fasching, R. 2007. Biodegradable micro-osmotic pump for long-term and controlled release of basic fibroblast growth factor. J Control Release, 124, 98–105. Santini, J. T., Jr., Cima, M. J. and Langer, R. 1999. A controlled-release microchip. Nature, 397, 335–338. Schneider, A. and Stieglitz, T. 2004. Implantable flexible electrodes for functional electrical stimulation. Med Device Technol, 15, 16–18. Schurr, M. O. 2007. Microsystems technology for medical applications. Minim Invasive Ther Allied Technol, 16, 75. Steeves, C. A., Young, Y. L., Liu, Z., Bapat, A., Bhalerao, K., Soboyejo, A. B. and Soboyejo, W. O. 2007. Membrane thickness design of implantable bio-MEMS sensors for the in situ monitoring of blood flow. J Mater Sci Mater Med, 18, 25–37. Stockl, D., Dewitte, K., Fierens, C. and Thienpont, L. M. 2000. Evaluating clinical accuracy of systems for self-monitoring of blood glucose by error grid analysis: Comment on constructing the ‘upper A-line.’ Diabetes Care, 23, 1711–1712.
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Tsai, H.-K. A. and Kulinsky, L. 2009. Integrating biosensors and drug delivery: a step closer toward scalable responsive drug-delivery systems. Adv Mater, 21, 656–660. Turner, A. P. and Pickup, J. C. 1985. Diabetes mellitus: biosensors for research and management. Biosensors, 1, 85–115. Vaddiraju, S., Tomazos, I., Burgess, D. J., Jain, F. C. and Papadimitrakopoulos, F. 2010. Emerging synergy between nanotechnology and implantable biosensors: A review. Biosens Bioelectron, 25, 1553–1565. Velten, T., Ruf, H. H. and Wackerle, M. 2005. Packaging of bio-MEMS: Strategies, technologies, and applications. IEEE Trans Adv Packag, 28, 533. Von Recum, A. and Jacobi, J. E. 1999. Handbook of Biomaterials Evaluation: Scientific, Technical, and Clinical Testing of Implant Materials, Philadelphia, PA, Taylor and Francis. Wang, X., Kim, K., Wang, Y., Stadermann, M., Noy, A., Hamza, A. V., Yang, J. and Sirbuly, D. J. 2010. Matrix-assisted energy conversion in nanostructured piezoelectric arrays. Nano Lett, 10 (12), 4901–4907. Ward, W. K., Jansen, L. B., Anderson, E., Reach, G., Klein, J. C. and Wilson, G. S. 2002. A new amperometric glucose microsensor: In vitro and short-term in vivo evaluation. Biosens Bioelectron, 17, 181–189. Wilkinson, J. M. 2001. Medical applications of microsystems technology: News update. Med Device Technol, 12, 28–31. Williams, D. F. 1999. The Williams dictionary of biomaterials, Liverpool, Liverpool University Press. Wilson, G. S. and Gifford, R. 2005. Biosensors for real-time in vivo measurements. Biosens Bioelectron, 20, 2388–2403. Wisniewski, N., Klitzman, B., Miller, B. and Reichert, W. M. 2001. Decreased analyte transport through implanted membranes: Differentiation of biofouling from tissue effects. J Biomed Mater Res, 57, 513–521. Wisniewski, N., Moussy, F. and Reichert, W. M. 2000. Characterization of implantable biosensor membrane biofouling. Fresenius J Anal Chem, 366, 611–621. Zacheja, J., Clasbrummel, B., Binder, J. and Steinau, U. 1995. Implantable telemetric endosystem for minimal invasive pressure measurements. Medtech 95, Berlin, Germany. Ziaie, B., Baldi, A., Lei, M., Gu, Y. and Siegel, R. A. 2004. Hard and soft micromachining for BioMEMS: Review of techniques and examples of applications in microfluidics and drug delivery. Adv Drug Deliv Rev, 56, 145–172. Ziaie, B. and Najafi, K. 2001. An implantable microsystem for tonometric blood pressure measurement. Biomed Microdev, 285–292.
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Abstract: The development of in vivo sensors for continuous monitoring of human health conditions is an area of sustained scientific and technological interest. This chapter highlights the important trends and challenges for microelectromechanical systems (MEMS) and microsystem-based in vivo sensors. The interest in applying MEMS technology for biological applications has grown rapidly because of some of its unique features such as better performance, high sensitivity, fast responsiveness, temporal control, size, cost, and comparable feature sizes. Finally, issues relating to short-term (acute) and long-term (chronic) implantation, along with future prospects for the application of MEMS in implantable biosensors, are discussed. Key words: bioMEMS, implantable, biosensors, biocompatibility, smart microsystems.
3.1
Introduction
Medicine and biology are among the most promising and the most challenging fields of application for microelectromechanical systems (MEMS) and microsystem technologies. MEMS is a technology developed from integrated circuit manufacturing to create miniature sensors and actuators. Medical devices based on MEMS technology (called as bioMEMS) are currently being developed for a wide variety of in vivo and point-of-care applications. The interest in MEMS for medical applications has grown rapidly, with increased opportunities in areas such as implantable biosensors, pacemakers, immunoisolation capsules, and drug-delivery microchips. The goal of this chapter is to highlight the important concepts, opportunities, challenges, and current trends in implantable MEMS sensors. The fundamental objective of in vivo MEMS sensors is to (a) facilitate clinical diagnosis of human health conditions and/or (b) provide therapeutic modalities via closed-loop control. When MEMS sensors are combined with integrated processors and telemetry circuits, a number of physical, chemical, or biological variables within the human body can be monitored and can thereby allow for evaluation of an individual’s medical condition. With an ultimate goal, utilize the same device to administer an ‘ondemand’ therapeutic drug via a remote trigger (Santini et al., 1999). The MEMS devices were first used in medical applications in the early 1970s with the advent of the silicon-micromachined disposable blood 81 © Woodhead Publishing Limited, 2012
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pressure sensors (Blazer et al., 1971). Over the last decades, there has been an exponential growth in number of MEMS devices for biomedical applications (Kovacs, 1998). This exponential growth is primarily due to the fact that MEMS technology provides device miniaturization (Kovacs, 1998; Wilkinson, 2001; Ziaie et al., 2004; Schurr, 2007), better performance or functionality (Lee, 1999), efficient transduction processes, higher reaction rate, lower reagent consumption, lower weight, lower unit cost per device, and higher reliability (Kovacs, 1998). Furthermore, the developments in these devices have been driven by the inherent desire to better mimic human physiology and to improve the quality-of-life. The overarching vision for MEMS sensors and devices are to address the major global healthcare challenges such as an ever-aging population, patient-centered care, and affordable costs. As stated earlier, one of the most prominent medical applications for bioMEMS is the field of in vivo sensors and ‘on-demand’ drug-eluting implants. For example, in vivo biosensors have the ability to provide metabolite(s) level(s) continuously regardless of the patient’s physiological state (rest, sleep, exercise, etc.) and without any external intervention (Vaddiraju et al., 2010). It is quite obvious that miniaturization (using MEMS technology) is a key desirable requirement for in vivo devices. This is especially true for implants in very small organs or those that are inserted using minimally invasive surgery, where the maximum allowable size is restricted by the working channel diameter. An important example in this regard is in diabetes management, which at present relies on test strip data (using blood drawn from finger pricking). This procedure is not only invasive and painful but also is incapable of reflecting the overall trends and patterns associated with patient’s daily habits (Reach and Wilson, 1992). This led to large-scale research efforts focused on developing in vivo biosensors for continuous monitoring of various biologically relevant metabolites (Koschwanez and Reichert, 2007). The other classes of sensors that have been intensively researched include sensors for nerve stimulation capable of alleviating acute pain (Schneider and Stieglitz, 2004), sensors for detecting electric signals in brain (Hu and Wilson, 1997a, 1997b), and sensors for monitoring bioanalytes (O’Neill, 1994), intraocular pressure (IOP) monitoring (Ha et al., 2011), and drug-delivery microchips for controlled delivery at the site of pain and stress (Ryu et al., 2007). In general, in vivo devices are often complex systems and consist of multiple components such as sensors, power sources, control units, and modules for wireless communication, potentially resulting in bulky overall device architecture if appropriate packaging technologies are not used. Other packaging requirement is often the material used for construction. In other words, the materials that make intimate contact to biological matter under test have to be biocompatible to avoid unintentional effects on cells and tissues. In the
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case of in vivo sensors, the use of nonbiocompatible materials could potentially interfere with the biological subcomponents that in turn could affect the sensor stability and performance (Velten et al., 2005). For example, the sensors must be packaged and sterilized, and the resulting device must be biocompatible with the host system into which it is implanted. According to Madou, ‘Biocompatibility is the single most complex issue facing in vivo sensor development and it needs addressing up front in the sensor design’ (Madou, 2002). The reliability of in vivo systems are often undermined by a host of other factors such as biofouling (Wisniewski et al., 2001; Gifford et al., 2006) and foreign body response (Wisniewski et al., 2000), sensor drifts, and lack of temporal resolution (Kerner et al., 1993). The scope of this chapter is to discuss the current trends in MEMS in vivo sensors and the above-mentioned challenges in detail. This chapter aims to highlight the current trends of in vivo MEMS sensors with special emphasis on MEMS biosensors. In the following sections, various subsystems and few relevant case studies of in vivo sensors are discussed (Section 3.2). The chapter concludes with an outlook of the challenges and opportunities for MEMS-based in vivo sensors (Section 3.3).
3.2
Overview of MEMS in vivo devices and sensors
An in vivo biomedical system is any device that is intended to function inside the body for some period of time. A lot of work has been done in the application of MEMS technology for this purpose to adapt various types of sensors for in vivo applications (Amy and Langer, 2004). The aim of this section is to give a global overview of which MEMS- and microsystembased sensors are being used and how they are clinically applied for in vivo applications. The goal of short-term sensing of biological variables such as pH, analytes, and pressure in blood, tissue, and body fluids has largely been achieved, but stable sensors for long-term applications continue to elude researchers because of various reasons (Gough and Armour, 1995; Abel and von Woedtke, 2002). Long-term in vivo sensing is a critical component of an ideal closed-loop drug-delivery or monitoring system, but the issues of in vivo biocompatibility and biofouling are still being addressed in order to achieve in vivo sensing for longer periods. It is also essential that the degree of biocompatibility and minimal tissue response must be greater for sensor applications compared to other types of implants. All material systems irrespective of their biocompatibility produce some degree of tissue response. For example, implants can create partial isolation from the body. This typically does not impede the functions that are essentially mechanical in nature such as in case of drug-delivery systems, orthopedic, or tissue engineering applications. However, implant isolation can lead to greatly reduced sensitivity and increased response time in case of sensor
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applications. As the intimate interaction of sensor and analyte is inherent to the operation of in vivo sensors, the biocompatibility challenge in case of in vivo sensors remains the biggest stumbling block. In summary, efforts are currently under way to commercialize MEMS biosensors in vivo, especially for the less problematic short-term sensing applications, while challenges in long-term applications are being actively addressed. MEMS biosensors have incorporated various sensing strategies including electrochemical (Gough, 1988; Ward et al., 2002), mechanical (Piso and Veiga-Crespo, 2011), magnetic (Huang et al., 2009), and optical (McNichols and Cote, 2000) along with combinations of the above methods. For example, combined optical and electrochemical sensors have been developed to monitor local pH in brain tissue and in blood (Grant et al., 2000). Furthermore, multiparametric sensors have been reported that combines electrochemical and fiber-optic technology for continuous in vivo measurement of pH, carbon dioxide partial pressure, oxygen partial pressure, and oxygen saturation early in human pregnancy (Jauniaux et al., 1999). These illustrations indicate an important feature of MEMS that is their ability to operate in multiple modalities so that a broader utility can be leveraged.
3.2.1 Subsystems for in vivo sensors The various subsystems of a MEMS in vivo sensor are (a) the fabrication methodology, (b) the material used, (c) the packaging technology, (d) the power requirement, and (e) the communication system. Fabrication methodology: The fabrication process involves various bulk and surface micromachining techniques such as thin layer deposition, sacrificial layer etching, photolithographic patterning, and etching. Processes compatible with complementary metal oxide semiconductor (CMOS) allow integration with electronic circuitry. In some instances, ‘nontraditional’ fabrication processes from disciplines such as chemistry or biology are used, for example, in electrochemical sensors or surface coatings. Detailed discussion on these techniques can be found elsewhere in this book. Materials: The choice of materials for in vivo applications is limited due to stringent requirements of biostability and biocompatibility. Biostability means that the material must withstand the immune system of the body and biocompatibility means that the material must not cause any unwanted reactions in the body. A standard list of biocompatible and biostable materials does not exist, since the mechanisms involved depend on various complex details such as material processing, shape, finish, posttreatment, and impurities. While it is beyond the scope of this chapter to fully discuss material
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properties and issues, we briefly discuss some material compatibility challenges later in this chapter. Packaging technology: The human body is a very hostile and complex environment for foreign bodies that enter it, due to an active immune system. Therefore, the delicate parts of the sensor often need to be protected by a hermetic package. The electrical connections need to be routed by means of hermetic feedthroughs. Furthermore, the electrical conductors and interconnections outside of the hermetic package need to be also biostable. The readers are referred elsewhere for detailed discussions on hermetic protection, electrical feedthrough, interconnect, and conductors (Velten et al., 2005). In addition to package, coatings are used to improve the interface of the implant with the body organs (Ashammakhi and Tormala, 2004). The criteria for an excellent coating are their edge covering, peel resistance, and integrity of the coating film. In general, polymers are the most widely used coating material because of their comparable Young’s’ modulus and interfacial properties. Surface topology modifications can also provide the desired response of the body (Desai et al., 2000). Power requirements: In cases of autonomous chronic implants, power consumption is an important design constraint. Much of the development efforts have been invested in implantable batteries with sufficient longevity to address both continuous operation and small form-factor requirement. An interesting approach in this aspect is using electrostatic or piezoelectric conversion of mechanical vibrations. A capacitance or piezoelectric change due to external vibrations can cause current generation (Wang et al., 2010). In other approaches, implantable biofuel cells are also being investigated. Communication systems: It is essential that communication link with the in vivo sensor allows to either receive data concerning the sensor status or patient condition or to send data to the sensor to (re)program it. Recent advances in radio frequency (RF) systems have enabled detection from deep within the lossy medium of the body. Entirely passive circuits that are wirelessly connected to detect measurable changes have been implemented. An optical telemetry link to transmit data to an external controller is also a viable option.
3.2.2 Case studies of in vivo sensors As described earlier, the fundamental objective of in vivo MEMS sensors is to (a) facilitate clinical diagnosis of human health conditions and/or (b) provide therapeutic modalities via closed-loop control (Receveur et al., 2007). In addition to the previously stated challenges that need to be considered, the important design parameters for most in vivo sensors are power consumption, size, sensitivity, specificity, accuracy, and stability. We will begin
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our discussion on examples of in vivo sensors starting with the most common type of MEMS sensor – the pressure sensor. MEMS pressure sensors are mostly made by following the surface micromachining process. In this architecture, a suspended thin mechanical membrane is created by etching a sacrificial layer. The membrane deflection caused by pressure variations is transduced with the help of piezoresistors on the high-strain areas of the membrane and appropriate electronic circuitry. By using a CMOScompatible micromachining processes, readout circuitry can be integrated close to the sensor. MEMS pressure sensors have enormous potential for in vivo applications. A capacitance-based pressure sensor can be fabricated with the membrane deforming according to a pressure difference, causing a change in capacitance between the membrane and an electrode on the surface. For example, (Ziaie and Najafi, 2001) demonstrated a capacitancebased pressure sensor tested in vitro on a silastic tube made to mimic a pliable blood vessel. This system can be implanted in small mammals to measure blood pressure for hypertension and cardiovascular physiology. Pressure sensors Cardiovascular pressure sensors: Blood pressure at various anatomical positions contains clinically relevant information. Pressure proximal and distal to an occlusion can be measured to quantify its severity in terms of flow reserve (Pijls et al., 1993). Blood pressure can also be measured before and after a balloon catheter operation (Receveur et al., 2007). MEMS pressure sensors on catheters offer advantages over fluid-filled catheters with external transducers. They do not suffer from catheter whip, limited frequency response, and resonance. Due to their small size, these sensors can reach small places while yielding pressure readings comparable to reference sensors (Receveur et al., 2007). The continuous monitoring of pressure for cardiovascular applications using wireless implantable microsystems offers additional opportunities for better therapies and increased quality-of-life for a number of conditions such as heart failure, coronary artery disease, aneurysm, hypertension, and arrhythmias. For example, a passive wireless MEMS pressure sensor developed by CardioMEMS can monitor endovascularly repaired abdominal aortic aneurysms (Allen, 2005). This sensor consists of flexible plates bearing inductor windings (along with associated distributed capacitances) bound to a hermetically sealed reference cavity. The inductor windings serve two purposes: (a) forming a resonant electrical circuit with the capacitor and (b) magnetically coupling with an external loop. A change in the pressure surrounding the sensor will change the position of the plates, thereby changing the capacitance and resonant frequency of the sensor. The change in resonant frequency causes a change in the response of the external loop, which in turn is monitored by external
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electronics (Allen, 2005). In an another example, an implantable hemodynamic monitoring system containing a power source, integrated circuitry, a piezoelectric activity sensor, and a radiofrequency transmission coil hermetically sealed in a titanium can was developed to monitor chronic heart failure (Magalski et al., 2002). IOP sensors: Long-term, continuous IOP measurements offer a new perspective for patients suffering from glaucoma. Glaucoma is the loss of vision due to the damage of the optic nerve for which elevated IOP is an important risk factor. Chen et al. developed an implantable parylene-based wireless pressure sensor for continuous IOP monitoring in glaucoma patients (Chen and Tai, 2008). The sensor consists of electrical LC tank resonant circuit formed by an integrated capacitor and an inductor coil to facilitate passive wireless sensing using an external interrogating coil connected to a readout unit. Two surface-micromachined sensor designs incorporating variable capacitor and variable capacitor/inductor resonant circuits were implemented to realize the pressure-sensitive components. The sensor was monolithically microfabricated by exploiting parylene as a biocompatible structural material in a suitable form factor for minimally invasive intraocular implantation. Intracranial pressure sensors: For patients suffering from head injury or diseases such as chronic hydrocephalus or brain tumors, an increase in intracranial pressure is observed. In these cases, continuous measurement using a wireless implanted system offers the advantage of increased mobility, reduces the mortality risk, and enables continuous intracranial pressure monitoring to other adverse symptoms (Chapman et al., 1990). Using surface-micromachined polysilicon membranes for capacitive absolute pressure detection and monolithic integrated circuitry, an interdisciplinary consortium developed an implantable telemetric endosystem (Zacheja et al., 1995). Pressure sensors for other in vivo applications: A host of other medical conditions can also be monitored using MEMS pressure sensors. For example, urodynamic investigations to diagnose urinary problems involve interventions in the bladder and simultaneous measurements. Totally in vivo pressure monitoring systems would enable measurements under close to normal life circumstances for the patients. In other examples, a small pill-shaped biotelemeter is used for monitoring the health of a fetus during and after in utero fetal surgery. Finally, a miniaturized MEMS cell covered by a semipermeable diaphragm implanted microinvasively into the anterior chamber of the eye has been proposed as a glucose sensor (Receveur et al., 2007). Glucose sensors Diabetes mellitus is a worldwide public health problem. This metabolic disorder results from insulin deficiency and hyperglycemia and is reflected
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by blood glucose concentrations higher or lower than the normal range of 80–120 mg/dL (4.4–6.6 mM). The disease is one of the leading causes of death and disability in the world. Diabetic individuals are at a greater risk heart disease, stroke, high blood pressure, blindness, kidney failure, neurological disorders, and other health-related complications without diligent monitoring blood glucose concentrations (Turner and Pickup, 1985). To monitor glucose level using electrochemical principles, glucose oxidase (GOx) is immobilized on a microfabricated electrode. GOx is an enzyme that facilitates the oxidation of glucose to produce hydrogen peroxide. Micromachined electrodes have the advantages of fast response time, high reliability, and low cost due to mass production. However, the output current is very low because of its small size and difficulty in immobilizing GOx on the electrode surface. Therefore, the main technological challenges of these types of sensors are in the charge transfer mechanism and the GOx immobilization. Various groups have demonstrated electroenzymatic glucose sensors designed for implantation in subcutaneous tissue for continuous glucose monitoring (Johnson et al., 1992). At present, six minimally invasive blood glucose monitoring systems have been approved by the Food and Drug Administration (FDA) (Morais et al., 2010). Nevertheless, the longest in vivo functional lifetime of a marketed system is 7 days, and frequent calibration is required with handheld glucose meters. Despite outstanding advances in the in vitro functionality of such sensors, a reliable long-term and continuous glucose monitoring in vivo has not as yet been achieved due to the gradual loss of sensor functionality following implantation. Numerous investigators have suggested that glucose diffusion is negatively influenced by nonspecific protein adsorption from the tissue fluid to the sensor surface (Morais et al., 2010). Other examples of in vivo sensors The measurement of blood flow is relevant for the diagnosis of cardiovascular disease, for monitoring restenosis in stents, or for optimizing settings of pacemakers (Receveur et al., 2007). Steeves et al. (2007) designed a smart wireless sensing unit for noninvasive early stenosis detection in heart bypass grafts. Magnetic sensors are used to facilitate navigation during clinical procedures. One such system has a three-dimensional (3D) magnetic sensor embedded on a catheter. Strain sensors are used in dental care and orthopedics to monitor the status of tissue/bone implants. Melik et al. (2008) developed a passive, on-chip, RF-MEMS strain sensors that rely on the resonance frequency shift with mechanical deformation for the assessment of bone fractures. In summary, information from multiple sensors located on the tip of a catheter will ultimately help the doctor to improve diagnosis, monitor the procedure, and assess the effectiveness of therapy during procedures
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such as minimal invasive transvenous cardiological or neurological surgeries (Goosen et al., 2000).
3.2.3 Integrating biosensors and drug delivery The need for ‘on-demand’ individualized therapy has been a long held vision but largely unattainable goal. ‘On-demand’ drug-delivery systems will integrate biosensors capable of monitoring the levels of physiological parameters of a patient and, in response, trigger the release of drugs on a need basis, to customize drug administration and minimize harmful side effects. In other words, for effective individualized therapy, sensing of a biomarker indicative of a disease and subsequent delivery of the drug is essential. An ideal microfabricated in vivo drug-delivery system should integrate sensors and storage and release components into a self-regulating ‘smart’ device that could perform with minimal intervention (Tsai and Kulinsky, 2009). This being a challenging task can only be accomplished if each component is developed individually and optimized before full integration. Tsai et al. demonstrated a prototype drug-delivery device consisting of two parts: a molded PDMS drug/biosensor reservoir and a silicon substrate containing a drug-release valve. In this model system, Tsai et al. showed the integration of a biosensor for glucose employing glucose oxidase immobilized on a hydrogel contained within microfabricated vials of a device, which, in addition, contains a drugdelivery reservoir large enough (microliter volumes) to dispense therapeutic levels of protein biopharmaceuticals, such as insulin. The sensing element was stored in the microvial to be protected from continuous exposure to harsh environments (e.g., the human body), and, when desired, the lid of the valve can be opened, and the microsensor exposed to the stream of the marker/analyte. Once sampling and/or detection of the target marker were accomplished, the lid was closed again. The valve can then be reopened when an additional measurement is needed. In the drug-delivery application, the valve was open when a dose was required, and closed again after the desired amount was deployed (Tsai and Kulinsky, 2009).
3.3
Challenges and possible solutions to in vivo sensing methodology
Understanding the interaction between the implanted MEMS sensors and the local cellular environment and assessment of the immune response are critical for optimizing the performance of MEMS in vivo. In this section, we review the current understanding of the biocompatibility and foreign body response as applicable to MEMS in vivo sensors and examine the current strategies to improve the biocompatibility of MEMS.
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MEMS for biomedical applications Table 3.1 ISO 10993-1 and FDA biological response tests In vivo tests for tissue compatibility Initial evaluation steps Cytotoxicity Sensitization Irritation Intracutaneous reactivity Systematic toxicity (acute toxicity) Subchronic toxicity (subacute toxicity) Genotoxicity Implantation Hemocompatibility Supplementary evaluation steps Chronic toxicity Carcinogenicity Reproductive and developmental toxicity Biodegradation Source: Morais et al. (2010).
Table 3.2 Materials, sensors, and devices relevant to in vivo assessment of tissue compatibility In vivo assessment of tissue compatibility Material(s) of manufacture Intended additives, process contaminants, and residues Leachable substances Degradation products Other components and their interactions in the final product Properties and characteristics of the final product Source: Morais et al. (2010).
3.3.1 MEMS biocompatibility Biocompatibility is defined by The Williams Dictionary of Biomaterials as ‘the ability of a material to perform with an appropriate host response in a specific application’ (Williams, 1999). However, the biocompatibility requirements vary considerably depending on the device function and design. The performance of sensors (glucose, pH, etc.), for example, is limited by biofouling and isolation of the sensor surface. However, neural electrodes must remain in intimate contact with the neurons that they are stimulating or recording. In general, for all in vivo measurements, the implanted sensor perturbs the environment and initiates a response. This can translate into approximately 50% loss of sensitivity in vivo as compared to in vitro values (Stockl et al., 2000). Recent works have made it clear that biocompatibility does not mean that an implant is inert. Rather biocompatibility has been
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defined operationally as: minimal perturbation of the in vivo environment and similarly the in vivo environment does not adversely affect the sensor performance (Von Recum and Jacobi, 1999). Any device intended for long-term in vivo applications has to fulfill rigorous biocompatibility and biostability requirements (Anderson and Langone, 1999). First, it should not induce toxicity in the surrounding tissues and should not damage the local tissue due to induced mechanical stresses. Second, the drug-eluting capabilities of the MEMS device should not be compromised by the surrounding tissue. Specifically, the implant must tolerate long-term exposure to the physiological environment, as well as resist the impact of the surrounding tissue on its function (biofouling) (Ratner, 2004). The ISO 10-993 standards outline minimum tests of material characterization, toxicity, and biodegradation that may be augmented depending on actual device/sensor usage (Table 3.1). The general principles that may apply to the biological evaluation of materials, sensors, and devices are described in Table 3.2 (Morais et al., 2010).
3.3.2 Biofouling and surface modification The ultimate utility of many implantable MEMS sensors may be limited by another device–biological environment challenge – namely, biofouling. The adsorption of biomolecules (peptides and proteins) followed by cells frequently leads to device fouling and failure. Large-scale research efforts are being devoted toward developing methods to substantially reduce the phenomenon and produce devices that do not promote biofouling, yet retain their biocompatibility. This effort often takes the form of surface chemical modification of the device. Several recent reviews cover general issues in bioadhesion and protein adsorption (Blawas and Reichert, 1998). Chemical modification to reduce biofouling falls into one of two general methods. The first method uses surface-immobilized polymers that reduce the adsorption of biological materials. The second method relies on the self-assembly process to passivate the MEMS device surface (Ratner, 2004).
3.3.3 Foreign body response A foreign body response based on nonspecific protein adsorption, immunity, and inflammatory cells occurs under normal physiological conditions in order to protect the body from the foreign object, in this case the in vivo sensor. The acute inflammatory response starts immediately after the sensor is implanted. During the initial acute response, fluid carrying plasma proteins and inflammatory cells migrates to the site of the sensor. The proteins are adsorbed initially and then phagocytic cells (neutrophils, monocytes, and
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macrophages) surround the biosensor and attempt to destroy it. However, because a biosensor is relatively large, only ‘frustrated phagocytosis’ occurs, seen as the release of reactive oxygen species and enzymes intended to degrade the implant (Wilson and Gifford, 2005). The exact timing, action, and intensity of the process are dependent on the nature of the foreign body, which relates to size, shape, and physical and chemical properties. The acute response lasts normally about 3 days after which a chronic inflammatory response may set in or a modified version of the healing process will begin. Ultimately, a fibrotic capsule is formed, which is the hallmark of the foreign body response (Wilson and Gifford, 2005). This fibrous wall confines the implant and consequently prevents it from interacting with the surrounding tissue. To overcome the limited in vivo functionality and longevity of implantable sensors, some important approaches include biocompatible material coatings, steroidal and nonsteroidal anti-inflammatory drugs, and angiogenic drugs (Morais et al., 2010).
3.3.4 Sensor performance criteria The challenge for in vivo biosensors is to provide adequate performance to distinguish among other entities in a manner that leads to enhanced understanding of the biological function (Wilson and Gifford, 2005). That requires sensor specificity with appropriate spatial and temporal resolution within acceptable sensitivity and limits of detection (LOD) for each analyte. It is also necessary to achieve optimum balance among the figures of merit for a specific application. In addition, the biosensor must be reasonably stable, which is longer than a few hours, with days or weeks preferable. The minimum useful stability is defined by the duration of the experiment, which for in vivo applications may be hours or days in a hostile environment.
3.4
Regulatory dimensions
Medical products, of which sensors are a subset, are subject to many regulatory controls. The FDA and European Community determine whether a product is fit for sale in the United States and Europe, respectively. It is critical to understand the fundamentals of current regulatory procedures because of the complexity of obtaining product approval. Additionally, relevant procedures and guidance have been evolving extensively in the last several years. Historically, bioMEMS have had design cycles between 5 and 15 years long. Lengthy sets of clinical trials can be avoided if MEMS sensors can be applied to existing medical tools and do not claim to alter the performance. The regulatory body classifies medical devices based on the same criteria, which includes device category, placement on or in the
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body, and duration of contact with the body. An implantable biosensor is classified as an implantable device that will contact body tissue or bone for more than 30 days (United States Pharmacopeial Convention). Based on the classification of the device, the appropriate tests need to be determined from the test selection matrix. Once identified from the matrix, the corresponding test standards should be identified and followed as outlined. The readers are referred elsewhere for the summary of recommended tests (Koschwanez and Reichert, 2007). These guidelines are in accordance with the device categories and suggested biological testing set forth by the FDA.
3.5
Conclusions and future trends
This chapter has provided a general and broad overview of MEMS sensors for in vivo applications. MEMS have many characteristics that make them appealing for medical and biological applications. However, a host of biological challenges need to be addressed for reliable in vivo performance. Furthermore, in vivo sensors have to interface to the biological environment in order to function, and since the body is an active and complex system trying to control this interface, achieving the requirements on the different aspects is often challenging especially for chronic (long-term) applications. However, the clinical advantages are driving the efforts aimed at overcoming these challenges. Apart from biological challenges, MEMS design criteria in terms of power consumption, size, sensitivity, specificity, accuracy, and stability also need to be considered. Other challenges include long development times, packaging, and biocompatibility and biostability. In summary, the growing interest in combining MEMS devices with biology, and in using microsystem technology for ‘on-demand’ drugdelivery systems, may ultimately lead the way to integrated MEMS-based systems that could augment or replace entire biological systems in the human body.
3.6
References
Abel, P. U. and von Woedtke, T. 2002. Biosensors for in vivo glucose measurement: can we cross the experimental stage. Biosens Bioelectron, 17, 1059–1070. Allen, M. 2005. Micromachined endovascularly-implantable wireless aneurysm pressure sensors: From concept to clinic. The 13th International Conference on Solid-State Sensors, Actuators and Microsystems, Seoul, Korea, June 5–9, 2005. Amy, C. and Langer, R. 2004. A BioMEMS review: MEMS technology for physiologically integrated devices. Proc IEEE, 92, 6–21. Anderson, J. M. and Langone, J. J. 1999. Issues and perspectives on the biocompatibility and immunotoxicity evaluation of implanted controlled release systems. J Control Release, 57, 107–113.
© Woodhead Publishing Limited, 2012
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Ashammakhi, N. and Tormala, P. 2004. From past to present and future is today: From inert to multifunctional biomaterials. J Craniofac Surg, 15, 897. Blawas, A. S. and Reichert, W. M. 1998. Protein patterning. Biomaterials, 19, 595–609. Blazer, E., Koh, W. and Yon, E. 1971. A miniature digital pressure transducer, Proc 24th Ann Conf Eng Med Biol, 211. Chapman, P. H., Cosman, E. R. and Arnold, M. A. 1990. The relationship between ventricular fluid pressure and body position in normal subjects and subjects with shunts: A telemetric study. Neurosurgery, 26, 181–189. Chen, P.-J. and Tai, Y.-C. 2008. Microfabricated implantable parylene-based wireless passive intraocular pressure sensors. J Microelectromech Systems, 17, 1342–1351. Desai, T. A., Hansford, D. J., Leoni, L., Essenpreis, M. and Ferrari, M. 2000. Nanoporous anti-fouling silicon membranes for biosensor applications. Biosens Bioelectron, 15, 453–462. Gifford, R., Kehoe, J. J., Barnes, S. L., Kornilayev, B. A., Alterman, M. A. and Wilson, G. S. 2006. Protein interactions with subcutaneously implanted biosensors. Biomaterials, 27, 2587–2598. Goosen, J. F. L., French, P. J. and Sarro, P. M. 2000. Pressure, flow and oxygen saturation sensors on one chip for use in catheters. Proc. IEEE 13th Ann. Int. Conf. Micro Electro Mechanical Systems, Miyazaki, Japan, Jan 23–27, 537–540. Gough, D. A. 1988. Issues related to in vitro operation of potentially implantable enzyme electrode glucose sensors. Horm Metab Res Suppl, 20, 30–33. Gough, D. A. and Armour, J. C. 1995. Development of the implantable glucose sensor. What are the prospects and why is it taking so long? Diabetes, 44, 1005–1009. Grant, S. A., Bettencourt, K., Krulevitch, P., Hamilton, J. and Glass, R. 2000. Development of fiber optic and electrochemical pH sensors to monitor brain tissue. Crit Rev Biomed Eng, 28, 159–163. Ha, D., De Vries, W. N., John, S. W., Irazoqui, P. P. and Chappell, W. J. 2011. Polymerbased miniature flexible capacitive pressure sensor for intraocular pressure (IOP) monitoring inside a mouse eye. Biomed Microdevices, 14(1), 207–215. Hu, Y. and Wilson, G. S. 1997a. Rapid changes in local extracellular rat brain glucose observed with an in vivo glucose sensor. J Neurochem, 68, 1745–1752. Hu, Y. and Wilson, G. S. 1997b. A temporary local energy pool coupled to neuronal activity: fluctuations of extracellular lactate levels in rat brain monitored with rapid-response enzyme-based sensor. J Neurochem, 69, 1484–1490. Huang, S., Yang, H., Lakshmanan, R. S., Johnson, M. L., Wan, J., Chen, I. H., Wikle, H. C., 3rd, Petrenko, V. A., Barbaree, J. M. and Chin, B. A. 2009. Sequential detection of Salmonella typhimurium and Bacillus anthracis spores using magnetoelastic biosensors. Biosens Bioelectron, 24, 1730–1736. Jauniaux, E., Watson, A., Ozturk, O., Quick, D. and Burton, G. 1999. In vivo measurement of intrauterine gases and acid–base values early in human pregnancy. Hum Reprod, 14, 2901–2914. Johnson, K. W., Mastrototaro, J. J., Howey, D. C., Brunelle, R. L., Burden-Brady, P. L., Bryan, N. A., Andrew, C. C., Rowe, H. M., Allen, D. J., Noffke, B. W., et al. 1992. In vivo evaluation of an electroenzymatic glucose sensor implanted in subcutaneous tissue. Biosens Bioelectron, 7, 709–714. Kerner, W., Kiwit, M., Linke, B., Keck, F. S., Zier, H. and Pfeiffer, E. F. 1993. The function of a hydrogen peroxide-detecting electroenzymatic glucose electrode is markedly impaired in human sub-cutaneous tissue and plasma. Biosens Bioelectron, 8, 473–482.
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Koschwanez, H. E. and Reichert, W. M. 2007. In vitro, in vivo and post explantation testing of glucose-detecting biosensors: current methods and recommendations. Biomaterials, 28, 3687–3703. Kovacs, G. T. A. 1998. Micromachined Transducers Sourcebook, Boston, MA, WCB. Lee, A. P. 1999. Micro-Electro-Mechanical Systems (MEMS) – 1999, New York, NY, American Society of Mechanical Engineers. Madou, M. J. 2002. Fundamentals of Microfabrication: The Science of Miniaturization, Boca Raton, FL, CRC Press. Magalski, A., Adamson, P., Gadler, F., Boehm, M., Steinhaus, D., Reynolds, D., Vlach, K., Linde, C., Cremers, B., Sparks, B. and Bennett, T. 2002. Continuous ambulatory right heart pressure measurements with an implantable hemodynamic monitor: A multicenter, 12-month follow-up study of patients with chronic heart failure. J Card Fail, 8, 63–70. Mcnichols, R. J. and Cote, G. L. 2000. Optical glucose sensing in biological fluids: an overview. J Biomed Opt, 5, 5–16. Melik, R., Perkgoz, N. K. and Demir, H. V. 2008. Bio-implantable passive on-chip RF-MEMS strain sensing resonators for orthopaedic applications. J Micromech Microeng, 18, 115017. Morais, J. M., Papadimitrakopoulos, F. and Burgess, D. J. 2010. Biomaterials/tissue interactions: Possible solutions to overcome foreign body response. AAPS J, 12, 188–196. O’Neill, R. D. 1994. Microvoltammetric techniques and sensors for monitoring neurochemical dynamics in vivo. A review. Analyst, 119, 767–779. Pijls, N. H., Van Son, J. A., Kirkeeide, R. L., De Bruyne, B. and Gould, K. L. 1993. Experimental basis of determining maximum coronary, myocardial, and collateral blood flow by pressure measurements for assessing functional stenosis severity before and after percutaneous transluminal coronary angioplasty. Circulation, 87, 1354–1367. Piso, D. and Veiga-Crespo, P. 2011. Application specific integrated circuits in implantable sensors for monitoring intraocular pressure. Arch Soc Esp Oftalmol, 86, 311–313. Ratner, B. D. 2004. Biomaterials Science: An Introduction to Materials in Medicine, Amsterdam, Boston, Elsevier Academic Press. Reach, G. and Wilson, G. S. 1992. Can continuous glucose monitoring be used for the treatment of diabetes. Anal Chem, 64, 381A–386A. Receveur, R. A. R., Lindemans, F. W. and De Rooij, N. F. 2007. Microsystem technologies for implantable applications. J Micromech Microeng, 17, R50–R80. Ryu, W., Huang, Z., Prinz, F. B., Goodman, S. B. and Fasching, R. 2007. Biodegradable micro-osmotic pump for long-term and controlled release of basic fibroblast growth factor. J Control Release, 124, 98–105. Santini, J. T., Jr., Cima, M. J. and Langer, R. 1999. A controlled-release microchip. Nature, 397, 335–338. Schneider, A. and Stieglitz, T. 2004. Implantable flexible electrodes for functional electrical stimulation. Med Device Technol, 15, 16–18. Schurr, M. O. 2007. Microsystems technology for medical applications. Minim Invasive Ther Allied Technol, 16, 75. Steeves, C. A., Young, Y. L., Liu, Z., Bapat, A., Bhalerao, K., Soboyejo, A. B. and Soboyejo, W. O. 2007. Membrane thickness design of implantable bio-MEMS sensors for the in situ monitoring of blood flow. J Mater Sci Mater Med, 18, 25–37. Stockl, D., Dewitte, K., Fierens, C. and Thienpont, L. M. 2000. Evaluating clinical accuracy of systems for self-monitoring of blood glucose by error grid analysis: Comment on constructing the ‘upper A-line.’ Diabetes Care, 23, 1711–1712.
© Woodhead Publishing Limited, 2012
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Tsai, H.-K. A. and Kulinsky, L. 2009. Integrating biosensors and drug delivery: a step closer toward scalable responsive drug-delivery systems. Adv Mater, 21, 656–660. Turner, A. P. and Pickup, J. C. 1985. Diabetes mellitus: biosensors for research and management. Biosensors, 1, 85–115. Vaddiraju, S., Tomazos, I., Burgess, D. J., Jain, F. C. and Papadimitrakopoulos, F. 2010. Emerging synergy between nanotechnology and implantable biosensors: A review. Biosens Bioelectron, 25, 1553–1565. Velten, T., Ruf, H. H. and Wackerle, M. 2005. Packaging of bio-MEMS: Strategies, technologies, and applications. IEEE Trans Adv Packag, 28, 533. Von Recum, A. and Jacobi, J. E. 1999. Handbook of Biomaterials Evaluation: Scientific, Technical, and Clinical Testing of Implant Materials, Philadelphia, PA, Taylor and Francis. Wang, X., Kim, K., Wang, Y., Stadermann, M., Noy, A., Hamza, A. V., Yang, J. and Sirbuly, D. J. 2010. Matrix-assisted energy conversion in nanostructured piezoelectric arrays. Nano Lett, 10 (12), 4901–4907. Ward, W. K., Jansen, L. B., Anderson, E., Reach, G., Klein, J. C. and Wilson, G. S. 2002. A new amperometric glucose microsensor: In vitro and short-term in vivo evaluation. Biosens Bioelectron, 17, 181–189. Wilkinson, J. M. 2001. Medical applications of microsystems technology: News update. Med Device Technol, 12, 28–31. Williams, D. F. 1999. The Williams dictionary of biomaterials, Liverpool, Liverpool University Press. Wilson, G. S. and Gifford, R. 2005. Biosensors for real-time in vivo measurements. Biosens Bioelectron, 20, 2388–2403. Wisniewski, N., Klitzman, B., Miller, B. and Reichert, W. M. 2001. Decreased analyte transport through implanted membranes: Differentiation of biofouling from tissue effects. J Biomed Mater Res, 57, 513–521. Wisniewski, N., Moussy, F. and Reichert, W. M. 2000. Characterization of implantable biosensor membrane biofouling. Fresenius J Anal Chem, 366, 611–621. Zacheja, J., Clasbrummel, B., Binder, J. and Steinau, U. 1995. Implantable telemetric endosystem for minimal invasive pressure measurements. Medtech 95, Berlin, Germany. Ziaie, B., Baldi, A., Lei, M., Gu, Y. and Siegel, R. A. 2004. Hard and soft micromachining for BioMEMS: Review of techniques and examples of applications in microfluidics and drug delivery. Adv Drug Deliv Rev, 56, 145–172. Ziaie, B. and Najafi, K. 2001. An implantable microsystem for tonometric blood pressure measurement. Biomed Microdev, 285–292.
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