No Strings Attached

No Strings Attached

© PHOTODISC

Mohamed Mahfouz, Gary To, and Michael Kuhn

T

he microwave community has recently seen a large increase in the research being done pertaining to medical applications. A few example applications include • remote patient monitoring vital sign detection [1] • wireless implantable devices for endoscopy, pacemakers, brain computer interface, etc. [2] • an intracranial pressure implant [3] • hyperthermia for treating breast and prostate cancer [4]. For examples of many others, see [5]–[18]. Bioinstrumentation is one of the fastest growing industries, providing numerous solutions from clinical equipment to life-sustaining medical implants. Advancements in sensor technologies and innovation in computerization have spawned a vast amount of new devices for numerous applications. Recently, the introduction of reliable low-cost, low-power wireless technologies has given rise to a new generation of medical devices, which can be connected through pervasive wireless sensor networks.

Mohamed Mahfouz ([email protected]), Gary To, and Michael Kuhn are with University of Tennessee, Knoxville, USA. Digital Object Identifier 10.1109/MMM.2011.942729 Date of publication: 15 November 2011

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1527-3342/11/$26.00©2011 IEEE

December 2011 Supplement

This article provides an overview of smart bioinstruments highlighting examples from industry and academia. Smart bioinstruments are broken down into various applications, including diagnostics, surgical, in vivo, remote patient monitoring, and indoor positioning. Each of these applications has unique requirements and constraints related to power, sensor performance, wireless transmitter and receiver front-ends, and antenna. Compared to [2], this article focuses on application driven design and provides expanded discussion beyond implantable devices to wireless systems designed for diagnostic, remote patient monitoring, surgical, and positioning/tracking applications.

Available Frequency Bands

different set of functional requirements. The requirements for a specific application can be defined by answering some basic questions such as: • What is the minimum requirement for data rate? • What is the maximum allowable latency of the application? • How many access points? • What kind of interference within the operational area? • How big is the coverage area? • What security measures are needed to protect patient’s information? • How to ensure performance reliability? These factors drive the choice of the wireless protocol to be used for these applications. Figure 1 provides an overview of different applications with examples including current research and commercial devices. Table 2 provides an expanded list of examples divided by application. Each application has unique requirements, which ultimately dictate the final system design. In vivo devices typically operate at lower frequencies (, 1 GHz) in order to avoid increased soft tissue losses [5], [16], [25], although in vivo systems are now being designed that operate at higher

Wireless medical devices have stringent requirements on the frequency bands in which they can operate. Table 1 highlights the different bands both in the United States and Europe, which can be used for indoor medical applications for both narrowband and ultrawideband (UWB) applications. UWB has available frequency bands from 3.1–10.6 GHz and 22–29 GHz in the United States. Only portions of that 3.1–10.6 GHz band are currently available in Europe. A number of telemetry bands exist in the United TABLE 1. Summary of licensed medical wireless frequency bands States, and both the United States and in the United States and Europe. Europe have instrumentation, scientific, Location Frequency Band Frequency and medical (ISM) bands available, mainly in the 300 MHz to 3 GHz range. As shown United States Instrumentation, scientific, 315 MHz in Table 1, in vivo telemetry applications medical typically use bands in the radio frequency United States Medical implant 402–405 MHz (RF) and lower microwave frequency range communication service for operation (i.e., 315 MHz, 402–405 MHz, Europe Instrumentation, scientific, 433.05–434.79 MHz and up to 1427–1432 MHz in the United medical States while Europe uses 433.05–434.79 United States Wireless medical telemetry 608–614 MHz MHz and 868 – 870 MHz). service

Smart Bioinstruments Smart bioinstrumentation is the offspring of the IEEE 1451 Smart Transducer Interface Standard and medical instruments [19]. It is achieved by enabling each sensing instrument with a network-capable application processor to provide local control and feedback, and at the same time, connecting each instrument to a higherlevel network for remote monitor, control, and analysis, thus infusing the sensing system with a higher level of cognitive ability or smarts. Smart instruments can be divided into five categories: diagnostics, surgical, in vivo, remote patient monitoring, and patient or asset tracking (indoor positioning). Each of these applications operates in a different indoor environment and has a


Europe

Instrumentation, scientific, medical

868–870 MHz (short range)

United States


902–928 MHz

United States

Wireless medical telemetry service

1,395–1,400 MHz

United States

Wireless medical telemetry service

1,427–1,432 MHz

Europe


2,400–2,483.5 MHz

United States


2,400-2,483.5 MHz

United States


5,150–5,875 MHz

United States

Ultrawideband

1–10.6 GHz

Europe

Ultrawideband

3.4–4.8 GHz

Europe

Ultrawideband

6–8.5 GHz

United States

Ultrawideband

22–29 GHz

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when compared to [32] (20 mW to 1–2 mW). The size of Diagnostic Devices Surgical Instruments diagnostic wireless systems can be much greater than in vivo devices and includes wearable devices such as belts or shirts. The application in [32] is to monitor children over a long time frame Steerable Wireless Intraoperative Ultra Wide(months or years) while [21] Swallowable Gait Analyzing Tensioner for Total Band Surgical Camera [20] Knee Arthoplasty [22] Navigation [23] Shoe [21] discusses a shorter time frame of diagnostic testing Remote Monitoring for clinical applications that g g Patient Monitoring Patient Tracking could last only a few minutes to an hour. The system in [21] updates at 100 Hz or more, while the one in [32] does not require such a high update rate, resulting in lower power consumption. Wireless Pulse Implantable RFID Tracker [26] Oximeter [24] Monitoring Wireless remote monitorDevice [25] ing systems typically have similar requirements to wireless diagnostic systems. As Figure 1. Applications for smart instruments, including diagnostics, surgical, remote shown in Table 2, the remote patient monitoring, and indoor positioning. monitoring systems outlined in [33] and [34] operate in the 2.4 GHz ISM band. In certain instances, they require frequencies such as the 2.4 GHz ISM band [3], [27]. higher data rates than the diagnostic gait systems The major constraints in vivo systems continue to (123 Mb/s versus 100–300 kb/s) mainly due to the face include power consumption, size, and operating transmission of biosignals such as the electrocardiorange. As shown in Table 2, typical operating ranges gram (ECG), electroencephalogram (EEG), temperaspan from 1 cm to 10 m. Active transmitters operating ture, respiration, etc. In some cases, remote monitoring around 300–400 MHz can achieve operating ranges of systems will only update at long intervals (10 s to 5–10 m while inductive links typically operate at dis1 min or more), which reduces power consumption tances of 50 cm or less. Higher frequency in vivo links and can allow battery life to be extended to months such as the 2.4 GHz ISM band can operate at 1–2 m. or even years. The application in [29] is for cardiac Most implantable devices have a form factor 1–2 cm2, monitoring over an extended time period of up to although this can be increased in certain cases such three months that dictates a lower power consumption as a device integrated into an orthopedic implant [25]. than the chest belt described in [34] (1 mW versus 400 Additional work done for in vivo systems includes mW), which is used for high update rate monitoring of a multibiosignal implantable system [28] and optian athlete over a shorter period of time of up to eight mizing interdigitated capacitor biosensors utilizing hours. An excellent overview of wearable medical microwaves for biomolecular sensing [29]. Optimizdevices is presented in [35], while [36]–[40] provides ing the inductive link through implantable coil design more information on wireless sensor networks for is discussed in [30] and [31]. medical applications, including body area networks. Diagnostic wireless bioinstruments have a much Security in wireless sensor networks is a major condifferent set of requirements when compared to in cern that has only been partially addressed in current vivo systems. As shown in Table 2, wireless threewireless sensor network technology. The distributed dimensional (3-D) gait motion systems can operate nature of wireless sensor networks requires more in bands such as the U.S. 900 MHz or 2.4 GHz ISM robust authentication and encryption schemes such bands [21], [32]. Operating ranges of these systems as the technique outlined in [41]. Wireless security need to be greater than in vivo devices and are typiwill continue to play a major role in whether there is a cally 100 m or more and made for indoor/outdoor widespread acceptance of wireless sensor networks in use. Power requirements can vary greatly dependthe medical field. ing on the duration for which the device is intended Table 2 provides a few examples of wireless surgito operate before battery replacement. For example, cal systems, including a ligament balancing spacer the system outlined in [21] is relatively high-power

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TABLE 2. Example commercial and research devices broken down by application. Data Rate/ Positioniong Average Power Accuracy

Biosensor

Application

Operating Range

Intracranial pressure [3]

In vivo

,1 m

2.4–2.48 GHz

12 mm diamter 10 mm height

141 mW

Not specified

None specified [5]

In vivo

2–10 m

402–405 MHz

3.88 mm2 (chip only)

25 mW at 1% duty cycle

75 kb/s

Multichannel neural [16]

In vivo

1 cm

70–200 MHz

14 mm 3 15.5 mm

14.4 mW Inductive

Up to 2 Mb/s

Multichannel pressure [25]

In vivo

50 cm

150 MHz

Form fitting to implant

5 mW inductive

1–2 Mb/s

Glucose monitoring [27]

In vivo

2m

2.4–2.48 GHz Zigbee

20 mm diameter 50 mm length

88 mW

250 kb/s

3-D gait motion [21]

Diagnostics

.500 m

916 MHz

35.6 mm 3 10 mm

10–30 mW (estimate)

115 kb/s

3-D gait motion [32]

Diagnostics

100 m

2.4–2.48 GHz Zigbee

30 mm 3 50 mm 3 12 mm

1.5 mW

250 kb/s

Cardiac monitoring [33]

Remote monitoring

50–100 m

2.4–2.48 GHz

50 mm 3 50 mm (approximate)

1 mW

,2 Mb/s

Cardiac, tilt, respiratory, temperature [34]

Remote monitoring

,30 m

2.4–2.48 GHz Bluetooth

Chest belt

400 mW (estimate)

,3 Mb/s

Ligament balancing [22]

Surgical

15–20 m

315 MHz

60 mm 3 20 mm 3 120 mm

28 mW

100 kb/s

Gamma radiation detector [42]

Surgical

5–10 m

2.4–2.48 GHz Bluetooth

14 mm diameter 24 cm length

300 mW (estimate)

,3 Mb/s

Personnel and asset tracking [43]

Wireless positioning

50 m

6–7 GHz Ultrawideband

36 mm 3 33 mm 3 13 mm

20 mW (estimate)

15 cm (2-D)

Personnel and asset tracking [44]

Wireless positioning

50 m

6.35–6.75 GHz Ultrawideband

40 mm 3 40 mm 3 20 mm

10 mW (estimate)

,30 cm (3-D)

Frequency

Size

block [21] and a gamma radiation detector [42]. Wireless surgical bioinstruments typically need to operate over a shorter operating range compared to diagnostic and remote monitoring systems (5–20 m compared to 100 m or more). Also, they only need to operate continuously during the surgery, allowing a battery lifetime of 24 hours or less. The ligament balancing spacer block [21] operates at 315 MHz since it will have to transmit signals in and around the knee during surgery, causing propagation conditions closer to in vivo. The gamma radiation detector [42] operates in the 2.4 GHz ISM band with a Bluetooth link and requires a higher bandwidth (3 Mb/s versus 100 kb/s) and more power (300 mW versus 28 mW) when compared to


the ligament balancing system. The size constraints of surgical devices is application specific (e.g. a wireless probe for the gamma radiation detector and a wireless space block for the ligament balancing wireless pressure sensor). The wireless propagation environment of the operating room typically contains many different pieces of medical equipment and a lot of metal which creates signifcant scattering and multipath interference and can reduce wireless operating ranges and increase the bit error rate, especially for narrowband systems. Consequently, UWB technology has gained interest for increasing performance of wireless surgical devices. Two different indoor wireless positioning systems are outlined in Table 2 [43], [44]. These are commercial

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systems from Pulse Location Systems [32] and Zebra Enterprise Solutions Inc. [44]. Both of them utilize UWB wireless technology and operate in the 6–7 GHz band. The tags consume low power (10–20 mW) and can last up to seven years depending on the update rate. They have comparable tag sizes for tracking assets (3–4 cm length and width) and can achieve wireless positioning accuracy of 15–30 cm. Both of them employ time difference of arrival (TDOA) for triangulating the two-dimensional (2-D) or 3-D position of the wireless tag. These systems have been used for industrial applications such as assembly line/ automation, commercial asset tracking applications (airports), and health-care applications for tracking personnel and assets in a hospital. There are a variety of indoor positioning systems that have been developed by research groups. This includes carrier-based UWB [45]–[48], impulse-based UWB [49], [50], and frequency modulated continuous wave [51]–[53]. Various triangulation techniques are used, including TDOA and angle of arrival. Typical accuracy levels range from 1–20 cm. Accuracy levels as high as 0.1 mm have been reported for a static experiment [45] and 5 mm for a 3-D dynamic experiment [47]. A recent push has been to develop complementary metal oxide semiconductor (CMOS) UWB transcievers that comply to the IEEE 802.15.4a specification using binary shift keying for digital modulation [54]–[56]. This reduces power consumption and size of the tag, opening up many new applications for UWB.

ment, including an embedded RF wireless sensing system. A fundamental component of a smart instrument is one or more biosensors, which are chosen or designed to convert biological or physiological parameters of interest into quantifiable electrical signals. The electronics of a smart instrument are built around the biosensor(s). One of the often overlooked electronic components is the multiplexer. With the advancement of microelectromechanical system (MEMS) sensors, the size of the sensor decreases dramatically, which enables the realization of large sensing arrays. Large arrays of sensors give higher spatial resolution to the system, which is strongly desirable. However, addressing these sensors in an effective manner becomes deadweight to the electronics. Multiple signal processing lines, cascaded multiplexing, and embedding of the multiplexers into application specific integrated circuits (ASIC) are some of the current strategies used in addressing large sensing arrays.

Wireless Propagation in Indoor Hospital Environments

Wireless tracking and communication technology in hospital environments such as the operating room are susceptible to a high level of scatterers and corresponding multipath interference. This can reduce operating range and wireless data rates. Also, it can degrade achievable accuracy for wireless positioning systems. The experiment from Clarke et al. provides quantitative data on how wireless real-time positioning systems perEmbedded Wireless Sensing form in the operating room [57], where there is noticable System Architecture degradation of narrowband systems in certain locations A generic smart instrument contains key building of the operating room due to multipath interference. blocks regardless of its application. Figure 2 shows UWB positioning systems are able to achieve higher the basic functional block diagram of a smart instruaccuracy and provide more robustness to multipath interference. Understanding indoor propagation channels has Analog-toTransmitter Digital Converter been a strong push in UWB Multiplexer, Filters, Biosensors research, including a compreAmplifiers hensive statistical channel Microcontroller model [58] and experimental Antenna FPGA measurements in different Power Unit Electronics Voltage/Current types of indoor environments, Reference including hospitals [11], [59], [60]. As discussed in [11], the operating room UWB channel Antenna as modeled by IEEE 802.15.4a, has severe multipath effects Data Acquisition Digital Signal similar to an industrial enviUnit Computer Processing Display ronment. The pathloss effects Receiver are not as severe as it is similar to a residential environment. This creates a challenging Figure 2. Block diagram of a smart instrument, including transmitter, receiver, and propagation environment computer display.

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Power Source

Data

Skin Implant Device Biosensors

Data Recovered Data

Rectifier

Class E Differential Power Oscillator

Voltage Regulator Electronics Power External Coil

Internal Coil

Figure 3. Overview of an in vivo smart instrument powered through inductive coupling.

for wireless signals even over short distances such as 2–5 m.

Applications In Vivo Systems Extra precaution is needed for sensors designed for in vivo applications. In vivo systems are difficult to remove once implanted. Given this fact, multiple backup strategies must be integrated into the system in the event of a single point failure. Redundancy of the sensing units can ensure failure of some of the sensors does not compromise the integrity of the system. The burden on the bandwidth from the additional units can also be circumvented with careful hardware design and sophisticated software algorithms. The human body is a harsh and hazardous environment, where temperature and body fluid can affect the optimal performance of the smart instrument. A typical approach for implantable devices is to isolate and protect the sensors within the implants. Special treatments such as a biocoating can also be applied to the implants to prevent bacteria adhesion to the implant surface, which may lead to infection [61], [62]. A biocoating is a thin layer of biocompatible material that can be coated on a sensor or implant with various coating technniques such as plasma sprays, chemical vapor deposition, or even manual dipping in a solution of biocoating material. In orthopedics, biocoatings such as calcium phosphate faciliate reattachment of an implant to a paitent’s bone. Specific coatings can also prevent restenosis and thrombosis. Biocoatings also play an important role in biochemical sensing [63]–[65]. It can protect a biosensor from fouling by other proteins. There are two common methods used to power an embedded RF system: a battery and inductive powering. Most current medical devices operate between 1.8–5 V, which can be powered with rechargeable batteries. In some instances, such as implantable devices,


it is impossible to replace the batteries, and inductive powering must be used. Figure 3 shows an example of an in vivo smart instrument powered through inductive coupling. Inductive powering uses two inductively coupled coils tuned to the same resonant frequency. The magnetic field generated from the external coil induces an ac voltage in the internal coil, which can be rectified and regulated for the implanted device [66], [67]. The carrier frequency of the system is usually around 1–15 MHz [68], [69]. This is due to safety concerns since high power from the electromagnetic field can cause dangerous heating of the tissues. IEEE standard C95.1-2005 uses specific absorption rate and maximum permission exposure as a guideline to ensure the safety of the telemetry system and dictates the use of a frequency below 16 MHz. With the introduction of the wireless communication system, more stringent criteria are needed for analog to digital converters (ADC). For a system designer, the selection of the ADC is to find a balancing point between resolution and speed. Wireless communication introduces another layer of complexity to the system design. Data rates, number of concurrently operating devices, and bandwidth of the wireless protocols have to be taken into consideration.

Wearable Medical Devices The current push in wireless medical devices is taking an existing legacy system, combining it with the available wireless technologies, and incorporating it into the existing wireless network infrastructure of the hospital. Ambulatory monitoring devices such as pulse oximeters, body temperature thermometers, respiration sensors, and blood pressure monitoring cuffs have already been integrated into many wireless patient monitoring systems as part of the hospital infrastructure. These instruments are typically implemented with transceivers that operate within the wireless medical telemetry service (WMTS) bands, while offsite remote monitoring communication, such as physicians’

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and emergency medical technicians’ cell phones and personal digital assistants (PDAs) are wirelessly linked with 802.11x protocols, as shown in Figure 4. One of the most attractive aspects for going wireless with medical instruments is that devices can be made wearable. For instance, the ECG machine used to be a workstation that prints the output onto a long strip of paper, which is not portable, making it inconvenient in transporting patients around the hospital and difficult to achieve continuous monitoring. A new generation of wearable ECG medical devices provides an easy and convenient solution for continuous cardiac activities monitoring [70]–[72]. Wearable ECG sensing nodes can be attached to the patients as they are admitted to the hospital, and they are monitored continuously during their entire stay [73], [74]. Additionally, computer algorithms on a remote monitoring station can detect abnormal cardiac activities and alert onsite medical professionals [74].

Remote Patient Monitoring These wireless medical instruments together enable a biowireless sensing network, which provides a large scale, high-quality convalescent surveillance system [75]. This type of system has gained significant attention recently with the success story of a wireless remote intensive care unit (ICU) monitoring system from the University of Massachusetts Medical Center [76]. The study shows lower mortality rates, shorter hospital and ICU stays, and lower rates of preventable complications with careful implementation of the remote patient monitoring network. A significant achievement from the recent growth of wireless technologies is the development of the mobile health system. Patients with chronic diseases such as diabetes require discipline in monitoring their blood glucose level. With decreasing manufacturing costs for electronics, wireless intelligent self-monitoring systems have become readily available to patients. Some of these systems include an insulin pump, where the

patient can use their cellphone or PDA to record and manage their blood glucose level [77].

Instrumented Implant Integrating wireless technologies with medical devices enables physicians and engineers to collect data within the human body, which was impossible a decade ago. Biomechanics of the human body puzzles many medical researchers as there is no way to directly measure and verify their theoretical hypotheses. Medical research institutes developed several instrumented implants with embedded sensors, electronics, telemetry, and inductive powering systems integrated into the joint replacement implant [25], [80]–[83]. Figure 5 provides examples of these systems for various joints in the human body. These implants give us valuable insight into the biomechanics of the joints. Load, stress, and motion patterns can be extracted to improve our understanding and develop implants with better performance. For in vivo medical devices like these implants, one of the biggest limitations is the signal attenuation from the soft tissues of the human body. The U.S. Federal Communications Commission (FCC) specified the Medical Implant Communication Service (MICS) band (402–405 MHz) to be specifically used for implant products. Other frequency bands used by medical research institutions include the intentional radiator frequency band at 174-216 MHz under the FCC restricted guidelines FCC 15.242, which limits the use of this frequency band to biotelemetry devices and only within a designated health-care facility.

Next Generation of Bioinstrumention As wireless sensing technologies infiltrated existing medical devices, new and innovative bioinstrumentation that takes advantage of the wireless technologies began to surface. Diagnostic and surgical instruments are two of the most competitive areas for the next generation of medical devices.

Wireless Gait Analysis System Monitoring Center Wireless ECG Monitoring System [78]

Wireless Medical Telemetry Service/ 802.11x Servers Health-Care Professionals

Wireless Pulse Oximeter [79]

Figure 4. Remote patient monitoring systems linked wirelessly to health-care professionals.

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The most commonly used diagnostic devices are medical imaging systems such as X-ray, computed tomography (CT), and magnetic resonance imaging (MRI). While these devices can produce accurate images for diagnosis, they may not be readily available due to high operating costs and, in some cases, limited hospital availability. Hence, the new challenge is whether it is possible to evaluate the patient’s condition


Orthoload [84] Ref. [25]

Orthoload [84]

Orthoload [84]

Ref. [25]

Figure 5. Implantable wireless joint replacements for the knee, hip, spine, and shoulder. with more portable and inexpensive wireless devices that can be used within a doctor’s office. For example, a gait lab with force plate is traditionally used to evaluate the condition of a patient’s ankle joint. Figure 6 shows an emerging wearable wireless medical device that uses a network of force sensors, accelerometers, and gyroscopes to determine the gait motion and load pattern, while all the sensors and electronics are fitted within the size of a shoe [85], [86]. The physician can obtain instant, realtime feedback as the patient walks around after putting on these diagnostic shoes.

Wireless Vibroarthography Diagnostic Device Another interesting diagnostic tool utilizes the vibration of a joint to understand its 3-D kinematics during motion, as shown in Figure 7. Rudimentary methods for this type of analysis include qualitative analysis with a stethoscope. It was not until recently that these vibrations were quantified for analysis. Static-null accelerometers detect the vibration from the joint during motion. Healthy and degenerative patients give off distinctly different signatures as they perform dif-


ferent activities [87],[88]. A network of these sensors can help localize specific degenerative regions. Wireless implementation of the system permits a high level of flexibility, allowing it to monitor a variety of joints under many weight-bearing activities.

Wireless In Vivo Kinematic Assessment and Visualization System In vivo tracking of the biomechanics typically involves using an x-ray video imaging device such as fluoroscopy [89]. After the patient performs the activities under fluoroscopic surveillance, the motion is recovered with an image registration technique, which places the 3-D models of the bone onto 2-D images from the X-ray video. A new approach to recover real time in vivo biomechanics was introduced recently with a constellation of A-mode ultrasound transducers and a set of inertial measurement units (IMU), which contain accelerometers, gyroscopes, and magnetometers, as outlined in Figure 8. The idea is to use the IMUs to track the relative transformation between two adjacent segments of the joint, while the constellation of ultrasound units registers the ex vivo

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Figure 6. Shoe sensor for evaluating the 3-D biomechanics of the ankle joint [21], [85]. to in vivo transformation. Each sensor in the IMU has its strengths and weaknesses in motion tracking, yet they can be used to compensate each other’s shortcomings with a specially designed sensor fusion algorithm [90], [91]. The outputs from the IMUs and the A-mode ultrasound transducers are transmitted wirelessly to the computer, where doctors can visualize the in vivo motion of the joint. Besides being a diagnostic tool, this instrument can be used to help the physician with small operations such as joint injection to relieve pain. Using B-mode ultrasound, the path of the injection needle can be tracked, while the joint space is dynamically updated.

Wireless Smart Surgical Instruments Traditional surgical instruments are specifically designed and made to fulfill certain functions during surgery such as allowing the surgeons to gain access to the operating area, removing biological tissues, or placing and aligning the implants. In recent years, there has been a drive towards atraumuatic and minimally invasive surgeries. Under these new surgical techniques, the incision is dramatically

0.15 0.1 0.05 0 −0.05 −0.1

reduced in size. For example, in orthopedics using a traditional knee replacement surgical protocol, the length of the incision is 10–12 in. Operating with the new minimally invasive approaches, the incision is reduced to 3–5 in. These techniques, however, severely limit the visibility for the surgeon. While this may not negatively affect the most experienced surgeons, it becomes more challenging for those who only perform a few surgeries per year. In order to tackle this problem, medical research organizations and companies are investing in improved devices and systems utilized in orthopedic computer assisted surgery. One example is an intraoperative assessment tool designed to provide quantitative feedback to the surgeon during total knee replacement surgery, shown in Figure 9 [94], [95]. One of the most difficult problems during total knee replacement is balancing the tension of the ligaments such that the implant is aligned properly within the joint. An array of MEMS pizeoresistive microcantilevers are used as strain gauges to map the area of interest. A high level of

Vibration “Signatures” from the Patelofemoral Compartment 0.15 0.1 0.05 −0.05 −0.1 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 ×104 Healthy

0

1

2

3 4 5 Degenerative

6 ×104

Figure 7. Portable vibration sensing device can be used to diagnose joint conditions.

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IMU Tracker

Miniature A-Mode Ultrasound Transducers

Ultrasound Injection Guidance Ultrasound 3-D Reconstructed Femur Probe

In Vivo Tracking

Needle Path Projection

Injection Needle

3-D Reconstructed Tibia

Ultrasound to CAD Scene Registration

Joint Relative Motion

3-D Reconstructed Tibia

Guidance Display

Figure 8. Next generation of medical instrumentation using wireless inertial measurement units (IMUs) and A-mode Ultrasound to recover in vivo kinematics, as well as dynamically tracking the joint space during joint injection [92], [93]. integration of electronics with ASIC can significantly reduce the size of the instrument such that it can be placed into the joint space to assess the condition. Additionally, to avoid cluttering the operating table with cables from the instrument, it is integrated with a wireless transmitter and chip antenna that operates in the 315 MHz band.

Surgical Navigation The instrumentation technology for computer assisted surgery has grown rapidly in recent years. One specific research area is to detect the 3-D location of instruments and implants as well as the operating region.

The fundamental 3-D tracking technologies currently used in computer assisted surgery orthopedic systems include optical and electromagnetic tracking systems. One example of an optical tracking system is the Polaris Spectra 3-D system from Northern Digital Inc. This optical tracking system is an industry standard that has found widespread use in computer assisted surgery, including minimally invasive surgeries in orthopedics [97]. The optical tracking system works by infrared light being reflected off of passive markers on the probe and then being received by two or more infrared cameras. The rated 3-D accuracy of the Polaris Spectra system is 0.25 mm root-mean-squared error (RMSE) for a single

315-MHz Wireless Module Piezoresistive Microcantilevers Embedded in Biocompatible Epoxy as Biosensor

Extension

Flexion

Balancing the Extension and Flexion Resection Gap Ensure Proper Alignment of the Implants

Wireless Intraoperative Surgical Instrument Application-Specific Integrated Circuit Allows LargeScale Electronics Integration

Figure 9. Wireless surgical instrument for assessing the tightness of the joint after resection to ensure balance loading on the implant. MEMS, ASIC, and wireless technologies are used to implement a complicated system within a limited space [22], [96].


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tracking systems range from 1220 cm, although accuracy as high as 0.1 mm has been reported among research systems [45]. Table 3 provides a comparison of a commercial optical tracking system and the UWB Passive tracking system developed at the University of TenTracker nessee [11], [47]. The operating ranges are similar, although the UWB system can operate up to 13 m, while optical tracking systems are limited to around User Interface 6 m. The main limitation of optical tracking systems is maintaining line-of-sight. The UWB system has multiple base stations, which allows operation to continue even if one link is blocked by utilizing redundant base stations in triangulating the tag position. Figure 10. Infrared optical tracking system used in picking The optical tracking system only has one receiver, 3-D points on a human bone during knee replacement surgery. and therefore has no redundancy built in. The optical tracker can achieve stable 3-D accuracy of 0.1–0.3 mm, making it the industry TABLE 3. Comparison of infrared optical tracking, standard in computer assisted surgery for electromagnetic, and ultrawideband tracking systems. orthopedic applications. The UWB tracking system can achieve 3-D accuracy of Operating Operating 3-D Positioning Technology Range Frequency Accuracy 225 mm dynamically. With an increase in accuracy of the UWB tracking system to Infrared optical 2–6 m 344–357 THz 0.1–0.3 mm 122 mm, it will become a viable alternatracking [97]–[99] tive to optical tracking systems, especially Electromagnetic

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