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application-specific integrated circuit (ASIC), designed and fabri- cated using the Texas ... a 20% lifetime risk of developing heart failure for both men and women [3]. ... Cyberonics, Inc., Houston, TX 77058 USA (e-mail: [email protected]). A. L. Chlebowski .... Instruments 130-nm CMOS process and custom made to feed.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 57, NO. 6, JUNE 2010

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Fully Wireless Implantable Cardiovascular Pressure Monitor Integrated with a Medical Stent Eric Y. Chow∗ , Member, IEEE, Arthur L. Chlebowski, Student Member, IEEE, Sudipto Chakraborty, Member, IEEE, William J. Chappell, Member, IEEE, and Pedro P. Irazoqui, Member, IEEE

Abstract—This paper presents a fully wireless cardiac pressure sensing system. Food and Drug Administration (FDA) approved medical stents are explored as radiating structures to support simultaneous transcutaneous wireless telemetry and powering. An application-specific integrated circuit (ASIC), designed and fabricated using the Texas Instruments 130-nm CMOS process, enables wireless telemetry, remote powering, voltage regulation, and processing of pressure measurements from a microelectromechanical systems (MEMS) capacitive sensor. This paper demonstrates fully wireless-pressure-sensing functionality with an external 35-dB·m RF powering source across a distance of 10 cm. Measurements in a regulated pressure chamber demonstrate the ability of the cardiac system to achieve pressure resolutions of 0.5 mmHg over a range of 0–50 mmHg using a channel data-rate of 42.2 kb/s. Index Terms—Biomedical applications of electromagnetic radiation, biomedical monitoring, biomedical telemetry, implantable biomedical devices. Fig. 1. Radiograph of stent implanted in the pulmonary artery of a live porcine subject and conceptual picture of cardiac pressure monitor sealed in a liquid crystal polymer package and integrated with a stent.

I. INTRODUCTION EART failure is generally regarded as the inability of the heart to provide adequate blood flow to the body [1]. This progressive disorder affects over 5 million people in the United States and around 15 million worldwide [2]. There is a 20% lifetime risk of developing heart failure for both men and women [3]. Mortality rates of 30%–40% during the first year after diagnosis have been published, and after 5 years, this percentage increases to 60%–70% [4]–[6]. Measurements of pulmonary arterial pressures are often used to diagnose and/or monitor heart failure, but are generally only limited to an acute clinical setting [7], [8]. Numerous companies including Boston Scientific, CardioMEMS, Inc., ISSYS Sensing Systems, Inc., Medtronic, Inc., and St. Jude Medical have recently been working toward the development of chronic implantable cardiac monitors [9]–[23].

H

Manuscript received August 19, 2009; revised November 18, 2009; accepted January 8, 2010. Date of publication February 17, 2010; date of current version May 14, 2010. This work was supported in part by SOLX, Inc., USA. Asterisk indicates corresponding author. ∗ E. Y. Chow was with the Brain Computer Interface Laboratory, Weldon School of Biomedical Engineering and School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907 USA. He is now with Cyberonics, Inc., Houston, TX 77058 USA (e-mail: [email protected]). A. L. Chlebowski and P. P. Irazoqui are with the Brain Computer Interface Laboratory, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907 USA (e-mail: [email protected]; [email protected]). S. Chakraborty is with the Communication Systems Laboratory, Texas Instruments, Dallas, TX 47907 USA (e-mail: [email protected]). W. J. Chappell is with the IDEAS Microwave Laboratory, School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907 USA (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TBME.2010.2041058

Unfortunately, most of these devices, such as Medtronic’s Chronicle, lack the versatility of placement. Since the placement of these devices in more optimal locations, such as in the pulmonary artery as shown in Fig. 1, is not feasible, estimations of the desired parameters are required. Some of the devices are passive, and thus, lack any internal data processing that would improve data integrity and most of the newer devices lack wellestablished surgical and delivery methods. This paper explores the novel idea of integrating a medical stent with a fully wireless implantable cardiac monitor to take advantage of their well-established delivery methods that allow for placement nearly anywhere in the circulatory system. The integration of a miniature cardiac pressure monitor with a stent takes advantage of the maturity of stent technology, its delivery procedure, and its versatility in terms of implant location. The stent is used in the device as both structural support and an antenna for simultaneous wireless telemetry and powering. In addition to monitoring heart failure and other forms of cardiovascular disease, this device can monitor the condition and operation of the stents themselves. Stents have a variety of applications and are most widely used in treating obstruction of blood flow in the cardiovascular system. Common problems with stents include restenosis and reocclusion. A 6-month study on 91 patients showed a 33% rate of restenosis and a 15% rate of reocclusion [24]. Newer technologies attempt to combat this problem with methods such as drug-eluting coatings; however, even with these preventative measures, these problems still occur without warning since little is known about the

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Fig. 2.

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Simplified schematics of (a) capacitance-to-time circuit (b) voltage regular with bandgap voltage reference, and (c) wireless transmitter.

performance of stents after initial placement [25]. A miniature pressure sensor integrated with a stent would provide clinicians with a method to monitor for signs of restenosis and reocclusion after implantation. Prior studies described in [26] and [27] used modeling software and in vivo experiments on porcine subjects to validate and quantify transcutaneous data and power transfer from a stent-based radiator implanted deep within a body. This study presents a complete wireless implantable cardiac pressure monitor, which consists of an application-specific integrated circuit (ASIC) and microelectromechanical systems (MEMS) sensor integrated with an FDA approved medical stent. Fig. 1 shows a sealed conceptual prototype, while the current implementation described in this study is larger due to the requirement of several discrete components. Zilver 635 self-expandable stents, provided by Cook Medical, are integrated with the device and act as both the holder to secure the implant and an antenna for wireless data and power transfer. The E1.3 N MEMS capacitive pressure sensor, provided by microFab Bremen, is used to convert pressure measurements into capacitance values and is fed into the ASIC for data processing and modulation onto a high-frequency carrier for wireless transmission. The ASIC is also responsible for voltage regulation, control logic, and RF powering. II. SYSTEM DESIGN The cardiac pressure-monitoring device presented in this paper is a fully wireless active low-power measurement system. The ASIC is designed using the Texas Instruments (TI) 130 nm process and consists of a sensor interface, voltage regulators and references, radio-frequency (RF) rectifier for remote powering, and wireless transmitter. A stent is integrated with the ASIC, which provides an antenna and allows for securing the implant to the vessel wall. A. Capacitance-to-Time Conversion A measurement technique is used in the sensor interface, which utilizes a nanoamp current to charge the MEMS ca-

pacitor converting capacitance variations to time changes. The capacitance-to-time circuit is shown in Fig. 2(a), where the top plate of the MEMS capacitive sensor is connected to the drain of a PMOS current source MP2 . The voltage on the MEMS capacitor is given by VM EM S =

tID M P2 CM EM S

(1)

where t is the time in which current is being sourced. ID M P2 , the drain current of the PMOS current source in saturation and accounting for channel length modulation, is given by ID

M P2

W (VSG M P2 − |Vtp |)2 L × (1 + λ (VDD − VD M P2 ))

= Kp

(2)

where Kp is the technology parameter equal to (1/2)µp Cox , λ is the channel-length modulation parameter of MP2 , and VD M P2 is the drain voltage of MP2 , which is equal to the voltage on the MEMS capacitor, VM EM S . Using (1) for VD M P2 in (2), the drain current is given by ID

M P2

=

Kp (W/L)CM EM S (1 − λVDD ) . CM EM S − λtKn (W/L)

(3)

Using (3) in (1) and solving for t gives t=

VM EM S CM EM S . Kp (W/L) (1 − λVDD + VM EM S λ)

(4)

When VM EM S reaches the threshold of the Schmitt trigger, the output switches logic levels from “high” to “low.” Setting VM EM S to this threshold in (4) gives the time it will take to charge the MEMS capacitor. This time between when the current source begins charging up the top plate and when it reaches the threshold is directly proportional to the capacitance of the MEMS sensor and thus the pressure. This block can be reset by setting the ‘‘rst’’ pin to a logic level “high” causing the NMOS transistor MN1 to drain out all the current from top plate of the MEMS capacitor.

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CHOW et al.: FULLY WIRELESS IMPLANTABLE CARDIOVASCULAR PRESSURE MONITOR WITH STENT

The full measurement circuit consists of two capacitance-totime circuits, as shown in Fig. 2(a). One circuit has the MEMS capacitive sensor and the other has a reference capacitor with a value that is equal to the base capacitance of the sensor. The current sources in the two capacitance-to-time circuits are matched and provide the equal currents to their corresponding capacitors. The MEMS sensor will always have an equal or larger capacitance compared to the reference capacitor resulting in a longer charge-up time. Digital gate logic is used to create a pulse that transitions to a logic level “high” after the reference capacitor charges up to the threshold of the Schmitt trigger. A short time later, when the MEMS capacitor node reaches the threshold of its Schmitt trigger, the pulse switches back to a logic level “low.” The reference capacitor will be an off-chip component and is necessary to account for variations in the base capacitance of the MEMS sensor. When taking each pressure measurement, the circuit first comes off of its “reset state” and the MEMS sensor and reference capacitors begin to charge up. The reference capacitor reaches the threshold of the Schmitt trigger first while the MEMS sensor takes a little more time to charge up to the same voltage. This time difference represents the MEMS capacitor variation and logic is used to convert the signals into a pulse, which can be wirelessly transmitted. The low-power consumption of this circuit is seen through an evaluation of its integration with our MEMS capacitor. The MEMS sensor has an average measured base capacitance of 5.23 pF (with a standard deviation of 0.0527 pF) and an average sensitivity of 6.64 fF/mmHg (with a standard deviation of 1.319 fF/mmHg). The PMOS current source is used to output current on the order of a few nanoamps but this current, as shown in (2), is initially greater and diminishes as the voltage on the MEMS sensor increases. The initial greater current levels allow the circuit to quickly charge-up the base capacitance of the sensor. As the end of the charge cycle is reached, the remaining capacitance, representing the pressure reading, is charged up with a smaller current value allowing for relatively larger time variations, and thus improved sensitivity. This effect is advantageous when considering low power, low delay, and sufficient sensitivity of the circuit because it charges up the larger base capacitances quickly while achieving sufficient time changes for the smaller pressure-dependent capacitance variation. A measurement period takes an average of 5 ms which is sufficient for our cardiac monitoring application as it achieves a 200 Hz sampling frequency. B. Voltage Regulator and References The voltage regulator is supplied by the dc source generated by the RF rectifier. A PMOS with operational amplifier feedback topology, shown in Fig. 2(b), is used to enable low dropout voltage operation, which maximizes the usable charge [28], [29]. An NMOS-based operational amplifier design is used with an NMOS current source in order to guarantee a constant overdrive voltage over the range of the supply. The regulator requires a reference that is stable across the voltage variations of the RF rectifier and so a modified form of the supply-independent

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reference circuit from [30] is used. Diode connected transistors are used in both branches to minimize area, by allowing for a smaller source-resistor, and reduce power consumption, while maintaining the desired reference voltage. C. Wireless Transmitter A 2.4-GHz wireless transmitter is designed using the Texas Instruments 130-nm CMOS process and custom made to feed the stent-based antenna, provide enough power to ensure successful data reception when implanted, and operate at low levels of current consumption. The transmitter is designed to operate within the 2.4 GHz ISM band whose frequency range, as allocated by the Federal Communications Commission in [31]. A voltage-controlled oscillator (VCO) is used to modulate the data using binary frequency-shift keying (BFSK). A complementary cross-coupled VCO topology, shown in Fig. 2(c), is used for its feasibility of on-chip implementation, relatively low phase noise, and low power consumption for comparable performance with other topologies [32]. The performance of the transmitter is substantially limited by the poor quality of on-chip inductors due to series resistive losses, capacitances to the nearby substrate, size constraints, and energy coupled to the lossy substrate [33], [34]. Several design and layout methodologies are implemented to maximize the quality factor (Q) of the inductor including the use of an octagonal spiral, a patterned ground shield, and a differential (symmetric) topology. A patterned ground shield, formed using strips of polysilicon layer, is implemented to isolate the inductor from the substrate reducing energy dissipation while minimizing image currents [34], [35]. A differential (symmetric) inductor topology is used to improve the Q-factor due to reduction in substrate resistance and increase in magnetic flux [35], [36]. Furthermore, the differential topology reduces the required area and the symmetry improves the overall phase noise of the differential VCO [37]. The final 200 µm × 200 µm inductor, designed and fabricated using the TI process, has a measured inductance of 3.37 nH and Q of 10.5. D. Radio-Frequency Wireless Powering Low frequency inductive powering, based on the coupling of magnetic fields, is often used in biomedical implants but this approach is limited due to the need for proximity and proper alignment between the primary and secondary coils [38]–[41]. Remote powering based on electromagnetic wave propagation allows for greater transfer distances and improved immunity to alignment issues. Wireless powering of the system presented in this work is done using a 3.7 GHz wave, which feeds an RF rectifier circuit through the antenna. A Cockcroft–Walton multiplier, oftentimes referred to as the Greinacher multiplier, is used in this study as the fundamental block of the RF rectifier circuit. The multiplier produces sufficiently high voltages with relatively low input power levels when compared with various other structures including the PMOS voltage multiplier, fullwave diode rectifier, and gate cross-connected bridge rectifier [42]. Two stages are implemented using the TI 130 nm process to further increase the output voltage and improve the overall

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efficiency. Increasing the number of stages further results in diminishing returns due to the current drain of later stages. Schottky diodes are chosen for the RF rectifier due to their superior high frequency performance and low forward-bias voltage. This 150–300 mV forward bias allows for rectification at lower input biases, which is desirable for low power operation. In typical CMOS processes, p-type regions have a work function that is nearly equal to that of the metal, which prevents the formation of a Schottky barrier [43]. The TI 130 nm E035 CMOS process has unique processing steps and proper silicide material to allow for the formation of p-type Schottky diodes. Silicide, formed by a direct metallurgical reaction, is used to ensure good adhesion, low contact resistance, and appropriate Schottky barrier height between silicon and the metal interconnect [44]. Using deep n-well technology, these diodes are fabricated with excellent isolation from the substrate.

Fig. 3. Photograph of bottom of LCP package showing the window etched out of the LCP to expose the MEMS sensor. A zoomed in view of the ACA shows the vertical columns that form electrical connections between the sensor and the LCP interconnects.

E. Antenna and Tissue Modeling To achieve a preliminary understanding of the interaction of the stent with biological tissue, models are developed using Ansoft’s high frequency structural simulator (HFSS). A first-order approximation model is done in [26] where the stent-based antenna is placed within a section of tissue with dielectric properties set to that of muscle. Note that this model does not account for various aspects including the entire body and different layers of heterogeneous tissue and bone but does provide a reasonable approximation of the near-field interactions. At 2.4 GHz, human muscle tissue has a measured conductivity of 1.705 S/m and a relative permittivity of 52.791 [45]–[47]. The thickness of the muscle section is set to 18 cm, which matches that of a typical male human chest [48]. The stent is positioned 3.5 cm from the front side of the tissue model to roughly represent the distance from the heart to the surface of the chest. An external receive antenna is positioned at distances up to 1 m away from the front surface of the tissue model. Both transmit and receive antennas are included in a single simulation to help capture some of the near field interactions between the antennas. The power reductions as a result of implantation, simulate in [26], only change by a few dB with variations in external receive antenna distance and averages about 45 dB. A more detailed chest model is presented in [27], which consists of layers of skin, fat, muscle and incorporates the lungs, parts of the respiratory tract, heart, and major veins and arteries from Ansoft’s Human Body Model. The organs and other biological models consist of measured frequency-dependent tissue properties from [45]–[47]. This stent is positioned 3.5 cm from the surface of the chest and the tissue-induced power loss, simulated in [27], is 31.3 dB. F. System Packaging and Integration With a Stent A biocompatible hermetic package is necessary for housing the electronics. Biocompatibility studies are performed on multiple materials including low-temperature Co-fired ceramic (LTCC), parylene, liquid crystal polymer (LCP), silicon, and alumina. Alumina is used as a baseline for the experiments since it is a commonly accepted biocompatible material [49], [50].

Four-week in vivo studies are done to evaluate inflammation and fibrous encapsulation. In comparison with all the other materials including alumina, LCP had the least damaging effects on the tissue and showed no inflammation at the end of the 4-week period. In comparisons of fibrous encapsulation with alumina, the encapsulation layer thickness around LCP was 43% less than that around alumina after 1 week, 75% less after 2 weeks, and over 97% less after 4 weeks. As a result, LCP is chosen for this study due to its excellent biocompatibility in addition to its flexibility and ease of processing. To facilitate fabrication, LCP with copper clad plastic between two metal layers provided by Rogers Corporation is used. The copper metal is removed from both sides of the LCP and gold traces are patterned on one side using sputtering, photolithography, and etching. The ASIC is bonded to the LCP through a thin flip-chip bonding process using anisotropic conductive adhesive (ACA) whose RF performance in bonding ICs is characterized in [51]. In order to expose the MEMS capacitor, a window is created in the LCP package using photolithography with a deep reactive ion etch (DRIE). The sensor is then bonded around the window using ACA, as shown in Fig. 3, and cured under a 1.5-T magnetic field to create conductive columns through the adhesive and achieve electrical connections and a hermetic seal. The biocompatible LCP package of electronics is then integrated with the Zilver 635 self-expanding stent. These particular stents are fabricated by Cook Medical with gold markers on the ends for precision placing. The gold markers are held in place with rings, which the LCP package is fastened to through a soldering method. Soldering to nitinol is done using a flux that effectively reduces both the nickel and titanium surface oxides but contains no high toxicity metals [52]. Gold–tin solder is used, which is resistant to peeling, has a high tensile strength, and ensures biocompatibility [52]. The single-ended transmitter output from the ASIC is directly connected to the end of the stent, while the ground reference is the ground plane on the chip and LCP-based PCB. This ground reference is relatively small compared to traditional ground planes; however, the situation

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CHOW et al.: FULLY WIRELESS IMPLANTABLE CARDIOVASCULAR PRESSURE MONITOR WITH STENT

Fig. 4.

Optical microscope picture of ASIC.

is necessitated by surgical requirements for the implant and experimental results show acceptable performance. A conceptual image of the final cardiac pressure monitoring system is shown in Fig. 1, although the functional implementation presented in this study is slightly larger. The LCP-packaged electronics resides on the outside of the stent and is sandwiched between the stent and the vessel wall after implantation. The MEMS sensor and ASIC along with the LCP-based package has a maximum thickness of 300 µm and the final dimensions of the package will be 3 mm × 6 mm. During implantation, the packaged electronics push the vessel wall slightly outward while the stent expands to its full cylindrical shape causing minimal interference with the blood flow. For the target 6 mm diameter pulmonary artery, the size of the package will expand the vessel cross section by about 4.8%. In the stent comparative restenosis (SCORES) study, performed on 1096 patients over 50 centers, the vessels implanted with self-expandable stents had a 12.8% average increase in cross-sectional area (CSA) [53]. Work done in [54], also replicated in the SCORES trial, intentionally remodeled vessels on a volume-to-volume scale compensates for neointima formation by expanding the CSA by up to 20%. Thus, the 4.8% increase in vessel CSA seen in the implantation of our device is relatively small compared to that experienced in typical angioplasty with stenting procedures [53], [54]. III. RESULTS AND DISCUSSION The cardiac monitoring ASIC is fabricated by Texas Instruments and an optical micrograph of the die is shown in Fig. 4. Test boards are used to test the performance of the capacitanceto-time measurement circuit, voltage regulators, transmitter, RF powering rectifier, and integration of the system as a whole including additional auxiliary circuitry. In vivo studies are done to quantify the electromagnetic effects of the tissue on wireless powering and data transfer.

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Fig. 5. Radiograph showing our stent-based transmitter and chest cavity of a live porcine subject.

A. Wireless Transmitter and In Vivo Studies The wireless transmitter is measured to consume about 812 µA and outputs −45 dB·m of power. To verify that this power level is sufficient for transcutaneous telemetry, in vivo studies are performed on 32–36 kg domestic pigs, as shown in Fig. 5. The surgical procedure follows the Purdue Animal Care and Use Committee (PACUC) approved protocol (PACUC No. 08-019). Anesthesia induction is done with a combination of Telazol (250 mg tiletamine and 250 mg zolazepam), ketamine (250 xmg), and xylazine (250 mg). Anesthesia is maintained with inhalation anesthetics composed of isoflurane (1.5%–4.0% oxygen) administered from a machine with vaporizer and waste gas ventilation system. Throughout the procedure, muscle tone, reflexes, respiration, temperature, ECG, and blood pressure are carefully monitored. The results from the in vivo studies validate the ability to receive signals from a transmitter implanted deep within a living porcine body. The in vivo data, reported in [26], shows that after implantation in a live test subject, the received power, when compared to the free space case, diminishes by 33–35 dB at a 3.5 cm implantation depth over transmission distances of 10 cm to 1 m. As a frame of reference, the sensitivity specifications of the IEEE 802.15.4 ZigBee standard are examined. Among communication protocols, ZigBee has the most similarities with our specifications as it is aimed at short range, low data rate, and low power RF telemetry. The minimum sensitivity for ZigBee at 2.4 GHz is −91 dB·m at a data rate of 250 kb/s [55], [56]. This value can be used as a worst-case scenario, for benchmarking purposes, because this sensitivity is poor compared to existing commercial receivers and other standards and the data rates far exceed what is needed for cardiac pressure measurements [57]–[59]. The -45 dB·m output of the ASIC transmitter outputs -80 dB·m after facing a 35 dB power loss through the

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tissue, which is sufficiently greater than the sensitivity of the ZigBee standard. The 2.4-GHz wireless-link frequency allows for sufficient data rates and potential compatibility with other communication standards, such as Bluetooth and ZigBee, but faces interoperability issues. The current continuous wave BFSK implementation is used to characterize propagation through the body and validate the wireless data-transfer in a controlled environment but is not necessarily appropriate for large-scale clinical use. Although the current communication scheme has a relatively low quality of service compared to other local, personal, and body area networks, it does have very low power requirements and implementation complexity [60]. For our system, a packet collision is not particularly problematic since large amounts of data are sent and postprocessing averaging is used to diminish the effects of these interference-based errors. The final implementation will utilize interference resistant methods such as frequency-hopping spread spectrum (FHSS), used in Bluetooth, direct-sequence spread spectrum (DSSS), used in ZigBee and Wi-Fi, or orthogonal frequency-division multiplexing (OFDM), used in Wi-Fi.

Fig. 6. (a) Measured performance of RF powering IC compared with the discrete component implementation. (b) Photograph of discrete component RF powering integrated with the system ASIC and MEMS capacitive sensor.

B. Radio-Frequency Wireless Powering Test-boards are integrated with a stent to quantify the performance of the RF powering IC. The circuit is most efficient in free space at frequencies from 2 to 4 GHz due to the dimensions of the stent-based antenna. A frequency of 3.7 GHz is chosen for testing and operation because it is sufficiently far from the transmit frequency of 2.4 GHz allowing for data reception after filtering. Measurements of the CMOS RF powering circuitry, taken with the device placed in front of the transmit antenna, show that it is unable to provide sufficient power to supply the full cardiac pressure monitoring system using reasonable levels, under 4 W, of external wireless power. Full system simulations with the RF powering were not feasible due to the nonavailability of Schottky diode models in this process and resulted in the inability of the CMOS rectifier to provide enough voltage to turn on the voltage regulator. To allow for comparison, the measurements plotted in Fig. 6(a) use a 1-kΩ resistor as the load, which is representative of the system when it is active. The results illustrate that the performance is insufficient for providing the 2.2 V required to supply the system using reasonable power levels. Extrapolating the data predicts that an RF power of about 43 dB·m (20 W) is required to turn on the system. The IC implementation described in this study demonstrates the feasibility of a CMOS-based GHz-frequency wireless powering scheme but optimizations are needed, for both the rectifier and the measurement circuitry, to achieve full functionality on a monolithic chip. To achieve an initial fully functional prototype, an RF powering module is assembled using discrete components. The key modifications are the use of Avago Technologies HSMS-286R Schottky diodes, 0201 capacitors, and a complementary architecture, which results in the doubling of the output voltage. The use of this complementary architecture and optimizations to the Schottky diode layouts would allow for similar performance

on CMOS. A test-board integrating the discrete component RF powering with the ASIC measurement system and transmitter, MEMS capacitor, and reference capacitor is assembled and connected to a stent, as shown in Fig. 6(b). The results of the discrete component RF powering integrated with the full system, plotted alongside the IC results in Fig. 6(a), are taken at a transmit distance of 10 cm. At an input power of about 22 dB·m, the rectified voltage first approaches 1.4 V and the voltage regulator starts to turn on and there is a drop in this voltage due to the increase in current consumption of the system. At about 35 dB·m (3.2 W), the RF powering circuit provides about 2.2 V and the voltage regulator stabilizes. For the rectified voltage range of 2.2–4.2 V, the regulated voltage has a standard deviation of 3.43 mV. An input power of 35.58 dB·m (3.6 W) results in a rectified voltage of 2.5 V and for the range from 2.5 to 4.2 V, the standard deviation decreases to 1.45 mV. Sufficiently reliable system performance is thus obtained with an RF power of at least 3.2 W at a distance of 10 cm with slightly improved reliability with power levels greater than or equal to 3.6 W. These power levels require an investigation of human safety in terms of exposure to this RF radiation. There are two established standards that specify regulations for human exposure to RF radiation: the IEEE Standard C95.1 developed by the IEEE International Committee on Electromagnetic Safety (ICES), which is recognized as an American standard by the American National Standards Institute (ANSI), and the International Commission on Nonionizing Radiation Protection (ICNIRP) guidelines [61], [62]. For the 3.7-GHz RF powering frequency, the 2–5 GHz subset of the two standards is examined. For the general public, both standards specify a local specific absorption rate (SAR) of 2 W/kg averaged over 10 g of tissue [61], [62]. The only significant difference between the two

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standards is the time period for which the SAR values are averaged, which is specified as 6 min by the ICNIRP guidelines and 30 min by the IEEE Standard C95.1 [61], [62]. The IEEE Standard C95.1 also specifies an instantaneous maximum permissible exposure (MPE) of 18.56(f)0.699 W/m2 where f is in GHz and between 3 and 30 GHz, resulting in an MPE of 46.318 W/m2 at 3.7 GHz [61]. In our experimental setup, the power density, using Friis path loss formula, at the surface of the chest with a 3.2 W transmit power at a distance of 10 cm is calculated to be 25.464 W/m2 [63]. This power density at the surface of the chest, which represents a maximum due to the attenuation of the field as it progresses deeper into the tissue, is sufficiently below the 46.318 W/m2 MPE specification. To estimate the average SAR of our experimental setup, a simplified 3-D model is developed, which incorporates layers of skin, fat, and muscle. The SAR of a tissue exposed to an electric field is given by SAR =

σE 2 2ρ

(5)

where σ is the conductivity of the tissue, E is the rms electric field, and ρ is the tissue density. The dielectric properties and densities of the various tissue layers are obtained from [45]–[47] and the corresponding thicknesses of skin and fat, described in [64] and [65], are set to 1 and 3 mm, respectively. Since muscle is the primary tissue near the surface of the chest region, its corresponding density of 1040 kg/m3 is used to approximate the cubic volume of a 10 g section to have a linear dimension of 2.126 cm. This volume, along with the tissue thicknesses and dielectric properties, is used to construct a 3-D model to determine the average SAR over a 10 g section of chest tissue. The simulation breaks the tissue section into 100 000 tetrahedra and calculates the power density, based on Friis path loss formula and attenuation due to tissue-absorption, and SAR of each piece [63]. The average simulated SAR of the three-layer tissue section with a 3.2 W, 3.7 GHz external power source at a distance of 10 cm from the chest surface is 2.2898 W/kg. This value is slightly greater than the 2 W/kg specified by both the IEEE C95.1 and ICNIRP guidelines; however, those specifications are averages over 30 and 6 min, respectively [61], [62]. The clinical use of our device will require sampling for only a few seconds at intervals of once every few weeks, so this application averages well below the safety guidelines, which would allow our system to continuously power and record for over 5 min. C. Capacitance-to-Time Conversion For the initial testing of the capacitance-to-time measurement circuit, variable capacitors are used to set both the reference and sensor capacitances. The capacitances are set using an automated stepper motor integrated with a custom made plastic screwdriver to precisely set the values. The capacitances are verified using an Agilent 4284 A Precision LCR Meter. The output of the capacitance-to-time measurement circuit is captured by probing the output after a buffering stage. The measured pulsewidths data shows that the greatest change in pulsewidth is when the difference between reference and sensor capacitances

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is below a few picofarads. The optimal choice of the reference capacitor value is the capacitance of the sensor, which corresponds to the low end of the pressure range. This choice of reference capacitance minimizes its capacitive difference with that of the sensor, producing the maximum change in pulsewidth for pressure variations, and minimizing the time required to complete a measurement. D. Integration of MEMS Sensor With ASIC The ASIC is integrated with the microFab Bremen E1.3 N MEMS capacitive sensor onto the test-board with external wires for probing, shown in Fig. 6(b). A reference capacitor with a value equal to the base value of the MEMS sensor and the corresponding capacitances are verified using an Agilent 4284 A precision LCR meter. The output of the capacitance-to-time circuit is fed directly into the wireless transmitter; however, for testing purposes, a test-pad is attached onto this intermediate node allows for monitoring of this signal. An external receiver is used to receive the wireless signal and perform demodulation to recover the data. The demodulated data is confirmed to be the same as the output of the capacitance-to-time circuit. The data is a pulse whose width corresponds to the MEMS sensor capacitance, which is dependent on the pressure. The pulsewidth is measured as a function of pressure and the rate-of-change of the corresponding trend-line is 47.4 µs/mmHg. This pulse is then modulated onto a high-frequency carrier through a BFSKlike scheme and wirelessly transmitted. The data rate of the channel between the implanted transmitter and external receiver determines the maximum resolution of the pulsewidth, and thus pressure, that our system can measure. The detectable changes in pressure are plotted as a function of data rate in Fig. 7(a) and show that to detect pressure changes of 0.5 mmHg, the wireless channel must support a data rate of at least 42.2 kb/s. This data rate is easily achieved and is relatively low compared to the ZigBee standard specification of 250 kb/s at 2.4 GHz and −91 dB·m sensitivity [55], [56]. The measured pressures, shown in Fig. 7(b), have the same trend as the simulated and actual values, although the exact values differ. A calibration constant of 0.593, derived from the data, is multiplied with the measured values to achieve a calibrated curve that matches closely with the actual pressures with an average error of about ±1.268 mmHg. E. Comparison With Current Products Similar miniature implantable devices for cardiac pressure monitoring are being developed by various companies including the two small startups CardioMEMS, Inc. and ISSYS Sensing Systems, Inc. CardioMEMS is developing a passive wireless pressure sensor that can be implanted in the patient’s heart chambers or in the pulmonary artery [11], [66], [67]. This passive technique, which utilizes an inductor–capacitor (LC) network whose resonant frequency is determined remotely, does not allow for on-board data processing or error correction methods. ISSYS has introduced an implantable, battery-less, telemetric sensor that is anchored in the left atrium and contains a MEMS pressure transducer, electronics, and an antenna that transmits

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IV. CONCLUSION AND FUTURE WORK This paper presents a fully wireless active platform for monitoring parameters in the vascular system such as cardiac pressure. A custom ASIC is designed and fabricated and enables wireless telemetry, RF powering, voltage regulation, and the processing of data from a capacitive sensor. The ASIC is packaged with a MEMS sensor, provided by microFab Bremen, into a biocompatible LCP-based package. A discrete component RF powering implementation is utilized in the prototype to optimize the wireless power transfer; however, in the final device, that block will be implemented on-chip. The package is then integrated with a medical stent, provided by Cook Medical, which acts as both an antenna and structural support. The utilization of a stent enables the advantageous use of well-established catheter-based surgical methods that allow for placement nearly anywhere in the circulatory system. Measurements done in a pressure chamber have shown the ability to achieve sensitivities of 0.5 mmHg over a pressure range of 0–50 mmHg above the atmospheric pressure. The precision and accuracy of these measurements are achieved due to the fact that the ASIC is an active system allowing for on-chip data processing. ACKNOWLEDGMENT Fig. 7. Plots of (a) detectable changes in pressure as a function of the data rate of the wireless channel and (b) measured performance with and without calibration alongside simulated results as a function of actual pressure.

data via magnetic coupling [14]–[16]. This device is still in the initial design phases but is very similar to our implant except for its use of magnetic coupling for data and power transfer, which limits the range to only a few centimeters and is very sensitive to external device placement. A few larger biomedical companies, including Boston Scientific, Medtronic, Inc., and St. Jude Medical, are also developing implantable cardiac pressure monitors. Boston Scientific who recently acquired Remon Medical Technologies, Inc. has developed the ImPressure sensor, an implantable hemodynamic monitor, which utilizes acoustic waves for activation and data transfer, and produces a curve corresponding to dynamic pressure variations [9]. The primary drawback of this device is its use of a piezoelectric-based pressure-sensing element, which has only the ability to measure dynamic and not static pressures [9], [10]. Medtronic, Inc. has developed a series of implantable hemodynamic monitors, including the IHM-0, IHM-1, and IHM-2 (Chronicle), that obtain estimates of PADP from the RV pressure tracings, which studies have shown these estimates have a correlation coefficient of only 0.8 [17]–[22]. Furthermore, these Medtronic devices are relatively large and their functional lifetime is limited by the battery [17]. St. Jude Medical recently acquired the HeartPOD technology from Savacor, Inc., which is an implantable sensor lead, coupled with a subcutaneous antenna coil, used to directly monitor left atrial pressure [68]. This device consists of a somewhat large implant (3.5 cm × 3.5 cm) and utilizes a lead extending to the target measurement location, which reduces reliability and complicates the surgical procedure [68].

The authors would like to thank Cook Medical for providing stents, Texas Instruments for their design help and fabrication services, microFab Bremen for providing MEMS pressure sensors, and their laboratory technician C. Ellison for his help in surgeries and IC dicing. REFERENCES [1] S. Simon, D. K. Moser, and D. Thompson, “Clinical assessment and investigation of patients with suspected heart failure,” in Caring for the Heart Failure Patient. Switzerland: Informa Healthcare, 2004, pp. 75– 92. [2] J. B. Young, “The global epidemiology of heart failure,” Med. Clin. North Amer., vol. 88, pp. 1135–1143, 2004. [3] Heart Disease and Stroke Statistics—2004 Update. Dallas, TX: American Heart Association, 2004. [4] K. K. Ho, J. L. Pinsky, W. B. Kannel, and D. Levy, “The epidemiology of heart failure: The Framingham Study,” J. Amer. Coll. Cardiol., vol. 22, pp. 6A–13A, 1993. [5] V. L. Roger, S. A. Weston, M. M. Redfield, J. P. Hellermann-Homan, J. Killian, B. P. Yawn, and S. J. Jacobsen, “Trends in heart failure incidence and survival in a community-based population,” J. Amer. Med. Assoc., vol. 292, pp. 344–350, Jul. 21, 2004. [6] M. R. Cowie, D. A. Wood, A. J. S. Coats, S. G. Thompson, V. Suresh, P. A. Poole-Wilson, and G. C. Sutton, “Survival of patients with a new diagnosis of heart failure: A population based study,” Heart, vol. 83, pp. 505–510, May 1, 2000. [7] W. Forssmann, “Die sondierung des rechten Herzens,” J. Mol. Med., vol. 8, pp. 2085–2087, 1929. [8] A. Cournand, “Cardiac catheterization: Development of the technique, its contribution to experimental medicine and its initial application to man,” Acta Med. Scand., vol. 579, pp. 3–32, 1975. [9] U. C. Hoppe, M. Vanderheyden, H. Sievert, M. C. Brandt, R. Tobar, W. Wijns, and Y. Rozenman, “Chronic monitoring of pulmonary artery pressure in patients with severe heart failure: Multicentre experience of the monitoring pulmonary artery pressure by implantable device responding to ultrasonic signal (PAPIRUS) II study,” Heart, vol. 95, pp. 1091–1097, 2009. [10] F. Springer, R. W. Gunther, and T. Schmitz-Rode, “Aneurysm sac pressure measurement with minimally invasive implantable pressure sensors: An alternative to current surveillance regimes after EVAR,” Cardiovasc. Intervent. Radiol., vol. 31, pp. 460–467, 2008.

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monitoring device,” in Proc. 4th Int. Symp. Wearable Comput., 2000, pp. 43–49. M. Merri, D. C. Farden, J. G. Mottley, and E. L. Titlebaum, “Sampling frequency of the electrocardiogram for spectral analysis of the heart rate variability,” IEEE Trans. Biomed. Eng., vol. 37, no. 1, pp. 99–106, Jan. 1990. W. Kluge, F. Poegel, H. Roller et al., “A fully integrated 2.4GHz IEEE 802.15.4 compliant transceiver for ZigBee applications,” in Proc. Int. Solid-State Circuits Conf., 2006, pp. 1470–1479. R. Roberts, “XtremeSpectrum CFP Document,” IEEE P802.15 Wireless Personal Area Networks, p802.15-03/154r1. Mar. 2003. IEEE Standard for Safety Levels with Respect to Human Exposure to Radio Frequency Electromagnetic Fields, 3 kHz to 300 GHz, IEEE Standard C95.1-2005 (Revision of IEEE Std C95.1–1991), pp. 0_1–238, 2006. A. Ahlbom, U. Bergqvist, J. H. Bernhardt, J. Cesarini, L. A. Court, M. Grandolfo, M. Hietanen, A. F. McKinlay, M. H. Repacholi, D. H. Sliney, J. A. J. Stolwijk, M. L. Swicord, L. D. Szabo, M. Taki, T. S. Tenforde, H. P. Jammet, and R. Matthes, “Guidelines for limiting exposure to time-varying electric, magnetic, and electromagnetic fields (up to 300 GHz). International commission on non-ionizing radiation protection,” Health Phys., vol. 74, pp. 494–522, 1998. C. A. Balanis, Advanced Engineering Electromagnetics. New York: Wiley, 1989, pp. 104–115. S. Salasche and G. Bernstein, Surgical Anatomy of the Skin. New York: Appleton & Lange, 1988. G. J. Tortora and B. H. Derrickson, Principles of Anatomy and Physiology, 11th ed. New York: Wiley, 2006. M. Allen, M. Fonseca, J. White, J. Kroh, and D. Stern, Implantable Wireless Sensor for Blood Pressure Measurement with an Artery. Atlanta, GA: CardioMEMS, Inc., 2005. J. Joy, J. Kroh, M. Ellis, M. Allen, and W. Pyle, Communicating With Implanted Wireless Sensor. Atlanta, GA: CardioMEMS, Inc., 2007. J. Ritzema, I. C. Melton, A. M. Richards, I. G. Crozier, C. Frampton, R. N. Doughty, J. Whiting, S. Kar, N. Eigler, H. Krum, W. T. Abraham, and R. W. Troughton, “Direct left atrial pressure monitoring in ambulatory heart failure patients,” Circulation, vol. 116, pp. 2952–2959, 2007.

Eric Y. Chow (S’07–M’10) received the B.S. degree from Cornell University, Ithaca, NY, in 2005, and the M.S. and Ph.D. degrees from Purdue University, West Lafayette, IN, in 2007 and 2009, respectively, all in electrical and computer engineering. He was engaged on four internships with Intel Corporation, during 2002, where his research was on both digital and analog group in wireless communications. He is currently with Cyberonics, Inc., Houston, TX, where he has been engaged in developing next generation implantable devices for treatment of epilepsy. His research interests include RF and low-power application-specific integrated circuit design, system integration of miniature implantable devices, and in vivo experimentation for applications including epilepsy, spinal cord injury, glaucoma, and cardiac disease.

Arthur L. Chlebowski (S’08) received the B.S. degree in biomedical engineering from Purdue University, West Lafayette, IN, in 2007. He is currently working toward the Ph.D. degree in biomedical engineering in the Brain Computer Interface Laboratory, Weldon School of Biomedical Engineering, Purdue University. During his undergraduate career, he developed sealing methods for biocompatible packages. His current research interests include biocompatibility testing, advanced package for biomedical implants, and the study of the correlation between glaucoma and blindness.

Sudipto Chakraborty (S’00–M’04) received the B.Tech. degree from Indian Institute of Technology, Kharagpur, India, in 1998, and the Ph.D. degree from Georgia Institute of Technology, Atlanta, in 2002. He has held several industry positions in Wipro Infotech, National Semiconductor, and IBM T. J. Watson Research Center. In 2004, he joined the Communication Systems Laboratory, Texas Instruments, Dallas, where he is currently engaged in advanced system-on-chip developments using siliconbased technologies, directed toward wideband wireless communication systems, and ultralow power biomedical telemetry devices. He has authored and coauthored several technical articles in IEEE conference and journals, books, and served in the technical program committee for various IEEE conferences and journals in the area of solid-state circuits, systems, microwaves, and communication systems.

William J. Chappell (S’98–M’02) received the B.S.E.E., M.S.E.E., and Ph.D. degrees in 1998, 2000, and 2002, respectively, all from the University of Michigan, Ann Arbor. He is currently an Assistant Professor at the IDEAS Microwave Laboratory, School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN. He is also a faculty Member of the Birck Nanotechnology Center and the Center for Wireless Systems and Applications, Purdue University. His research interests include silicon micromachining, polymer formation, and low-loss ceramics for high-frequency circuits and antennas, rapid prototyping, free-form fabrication, and small-scale formation of electrically functioning ceramic and polymer passive components. He has also been engaged in projects investigating RF design for wireless sensor networks, chemical sensors, and electrotextiles. Dr. Chappell was the recipient of the 2004 Joel Spira Outstanding Educator Award and been designated as a Teacher for Tomorrow in his department.

Pedro P. Irazoqui (S’94–M’03) received the B.Sc. and M.Sc. degrees in electrical engineering from the University of New Hampshire, Durham, in 1997 and 1999, respectively, and the Ph.D. degree in neuroengineering from the University of California, Los Angeles, in 2003. His Ph.D. work was on the design, manufacture, and packaging, of implantable integrated circuits for wireless neural recording. He was one of the founding Members and was the Vice President of IC development, Triangle Biosystems, Inc., Research Triangle Park, NC. He is currently an Assistant Professor in the Brain Computer Interface Laboratory, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, where his laboratory is engaged in the research on a modular approach to the design of biological implants in general and neural prosthetic devices in particular. These devices are being applied to the clinical treatment of physiological disorders, using miniature, wireless, implantable systems. The specific research and clinical applications explored in his laboratory include glaucoma, epilepsy, neural regeneration, and cardiac disease. Dr. Irazoqui was the recipient of the Best Teacher Award from the Weldon School of Biomedical Engineering in 2006, the Early Career Award from the Wallace H. Coulter Foundation in 2007, the Marion B. Scott Excellence in Teaching Award from Tau Beta Pi in 2008, and has been serving as an Associate Editor of IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING since late 2006.

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