Self-Powered Load Sensing Circuitry for Total Knee Replacement.

There has been a significant increase in the number of total knee replacement (TKR) surgeries over the past few years, particularly among active young and elderly people suffering from knee pain. Continuous and optimal monitoring of the load on the knee is highly desirable for designing more reliable knee implants. This paper focuses on designing a smart knee implant consisting of a triboelectric energy harvester and a frontend electronic system to process the harvested signal for monitoring the knee load. The harvester produces an AC signal with peak voltages ranging from 10 V to 150 V at different values of knee cyclic loads. This paper demonstrates the measurement results of a PCB prototype of the frontend electronic system fabricated to verify the functionality and feasibility of the proposed approach for a small range of cycling load. The frontend electronic system consists of a voltage processing unit to attenuate high peak voltages, a rectifier and a regulator to convert the input AC signal into a stabilized DC signal. The DC voltage signal provides biasing for the delta-sigma analog-to-digital converter (ADC). Thus, the output of the triboelectric harvester acts as both the power signal that is rectified/regulated and data signal that is digitized. The power consumption of the proposed PCB design is approximately 5.35 µW. Next, the frontend sensor circuitry is improved to accommodate a wider range of cyclic load. These results demonstrate that triboelectric energy harvesting is a promising technique for self-monitoring the load inside knee implants.

Single Exhale Biomarker Breathalyzer.

A single exhale breathalyzer comprises a gas sensor that satisfies the following stringent conditions: high sensitivity to the target gas, high selectivity, stable response over extended period of time and fast response. Breathalyzer implementation includes a front-end circuit matching the sensitivity of the sensor that provides the readout of the sensor signal. We present here the characterization study of the response stability and response time of a selective Nitric Oxide (NO) sensor using designed data acquisition system that also serves as a foundation for the design of wireless handheld prototype. The experimental results with the described sensor and data acquisition system demonstrate stable response to NO concentration of 200 ppb over the period of two weeks. The experiments with different injection and retraction times of the sensor exposure to constant NO concentration show a fast response time of the sensor (on the order of 15 s) and the adequate recovery time (on the order of 3 min) demonstrating suitability for the single exhale breathalyzer.

Novel Isoprene Sensor for a Flu Virus Breath Monitor.

A common feature of the inflammatory response in patients who have actually contracted influenza is the generation of a number of volatile products of the alveolar and airway epithelium. These products include a number of volatile organic compounds (VOCs) and nitric oxide (NO). These may be used as biomarkers to detect the disease. A portable 3-sensor array microsystem-based tool that can potentially detect flu infection biomarkers is described here. Whether used in connection with in-vitro cell culture studies or as a single exhale breathalyzer, this device may be used to provide a rapid and non-invasive screening method for flu and other virus-based epidemics.

Hybrid triboelectric-piezoelectric nanogenerator for long-term load monitoring in total knee replacements.

A self-powered and durable pressure sensor for large-scale pressure detection on the knee implant would be highly advantageous for designing long-lasting and reliable knee implants as well as obtaining information about knee function after the operation. The purpose of this study is to develop a robust energy harvester that can convert wide ranges of pressure to electricity to power a load sensor inside the knee implant. To efficiently convert loads to electricity, we design a cuboid-array-structured tribo-pizoelectric nanogenerator (TPENG) in vertical contact mode inside a knee implant package. The proposed TPENG is fabricated with aluminum and cuboid-patterned silicone rubber layers. Using the cuboid-patterned silicone rubber as a dielectric and aluminum as electrodes improves performance compared with previously reported self-powered sensors. The combination of 10wt% dopamine-modified BaTiO3 piezoelectric nanoparticles in the silicone rubber enhanced electrical stability and mechanical durability of the silicone rubber. To examine the output, the package-harvester assemblies are loaded into an MTS machine under different periodic loading. Under different cyclic loading, frequencies, and resistance loads, the harvester's output performance is also theoretically studied and experimentally verified. The proposed cuboid-array-structured TPENG integrated into the knee implant package can generate approximately 15µW of apparent power under dynamic compressive loading of 2200 N magnitude. In addition, as a result of the TPENG's materials being effectively optimized, it possesses remarkable mechanical durability and signal stability, functioning after more than 30 000 cycles under 2200 N load and producing about 300 V peak to peak. We have also presented a mathematical model and numerical results that closely capture experimental results. We have reported how the TPENG charge density varies with force. This study represents a significant advancement in a better understanding of harvesting mechanical energy for instrumented knee implants to detect a load imbalance or abnormal gait patterns.

Fabrication and Assembly Techniques for Sub-mm Battery-Free Epicortical Implants.

Over the past three decades, we have seen significant advances in the field of wireless implantable medical devices (IMDs) that can interact with the nervous system. To further improve the stability, safety, and distribution of these interfaces, a new class of implantable devices is being developed: single-channel, sub-mm scale, and wireless microelectronic devices. In this research, we describe a new and simple technique for fabricating and assembling a sub-mm, wirelessly powered stimulating implant. The implant consists of an ASIC measuring 900 × 450 × 80 µm3, two PEDOT-coated microelectrodes, an SMD inductor, and a SU-8 coating. The microelectrodes and SMD are directly mounted onto the ASIC. The ultra-small device is powered using electromagnetic (EM) waves in the near-field using a two-coil inductive link and demonstrates a maximum achievable power transfer efficiency (PTE) of 0.17% in the air with a coil separation of 0.5 cm. In vivo experiments conducted on an anesthetized rat verified the efficiency of stimulation.

Exhaled nitric oxide detection for diagnosis of COVID-19 in critically ill patients.

BACKGROUND: COVID-19 may present with a variety of clinical syndromes, however, the upper airway and the lower respiratory tract are the principle sites of infection. Previous work on respiratory viral infections demonstrated that airway inflammation results in the release of volatile organic compounds as well as nitric oxide. The detection of these gases from patients' exhaled breath offers a novel potential diagnostic target for COVID-19 that would offer real-time screening of patients for COVID-19 infection. METHODS AND FINDINGS: We present here a breath tester utilizing a catalytically active material, which allows for the temporal manifestation of the gaseous biomarkers' interactions with the sensor, thus giving a distinct breath print of the disease. A total of 46 Intensive Care Unit (ICU) patients on mechanical ventilation participated in the study, 23 with active COVID-19 respiratory infection and 23 non-COVID-19 controls. Exhaled breath bags were collected on ICU days 1, 3, 7, and 10 or until liberation from mechanical ventilation. The breathalyzer detected high exhaled nitric oxide (NO) concentration with a distinctive pattern for patients with active COVID-19 pneumonia. The COVID-19 "breath print" has the pattern of the small Greek letter omega (). The "breath print" identified patients with COVID-19 pneumonia with 88% accuracy upon their admission to the ICU. Furthermore, the sensitivity index of the breath print (which scales with the concentration of the key biomarker ammonia) appears to correlate with duration of COVID-19 infection. CONCLUSIONS: The implication of this breath tester technology for the rapid screening for COVID-19 and potentially detection of other infectious diseases in the future.

The Microbead: A 0.009 mm3 Implantable Wireless Neural Stimulator.

Wirelessly powered implants are increasingly being developed to interface with neurons in the brain. They often rely on microelectrode arrays, which are limited by their ability to cover large cortical surface areas and long-term stability because of their physical size and rigid configuration. Yet some clinical and research applications prioritize a distributed neural interface over one that offers high channel count. One solution to make large scale, fully specifiable, electrical stimulation/recording possible, is to disconnect the electrodes from the base, so that they can be arbitrarily placed freely in the nervous system. In this work, a wirelessly powered stimulating implant is miniaturized using a novel electrode integration technique, and its implanted depth maximized using new optimization design methods for the transmitter and receiver coils. The stimulating device is implemented in a 130 nm CMOS technology with the following characteristics: 300 µm × 300 µm × 80 µm size; optimized two-coil inductive link; and integrated circuit, electrodes and coil. The wireless and stimulation capability of the implant is demonstrated in a conductive medium, as well as in-vivo. To the best of our knowledge, the fabricated free-floating miniaturized implant has the best depth-to-volume ratio making it an excellent tool for minimally-invasive distributed neural interface, and thus could eventually complement or replace the rigid arrays that are currently the state-of-the-art in brain set-ups.

The Microbead: A Highly Miniaturized Wirelessly Powered Implantable Neural Stimulating System.

An implant that can electrically stimulate neurons across different depths and regions of the brain currently does not exist as it poses a number of obstacles that need to be solved. In order to address the challenges, this paper presents the concept of "microbead," a fully integrated wirelessly powered neural device that allows for spatially selective activation of neural tissue. The prototype chip is fabricated in 130-nm CMOS technology and currently measures 200 µm × 200 µm, which represents the smallest remotely powered stimulator to date. The system is validated experimentally in a rat by stimulating the sciatic nerve with 195-µs current pulses. To power the ultrasmall on-silicon coil, 36-dBm source power is provided to a highly optimized transmitter (Tx) coil at a coupling distance of 5 mm. In order to satisfy the strict power limit for safe use in human subjects, a pulsed powering scheme is implemented that enables a significant decrease in the average power emitted from the Tx.

Novel integration and packaging concepts of highly miniaturized inductively powered neural implants.

This work proposes solutions to the current bulky packaged neural implants. We describe the next generation of miniaturized wirelessly powered neural interface that are distributed and free floating in the nervous system. This paper focuses on the microassembly, hermetic packaging and its effect on the inductive power link.

Micropower Mixed-signal VLSI Independent Component Analysis for Gradient Flow Acoustic Source Separation.

A parallel micro-power mixed-signal VLSI implementation of independent component analysis (ICA) with reconfigurable outer-product learning rules is presented. With the gradient sensing of the acoustic field over a miniature microphone array as a pre-processing method, the proposed ICA implementation can separate and localize up to 3 sources in mild reverberant environment. The ICA processor is implemented in 0.5 µm CMOS technology and occupies 3 mm × 3 mm area. At 16 kHz sampling rate, ASIC consumes 195 µW power from a 3 V supply. The outer-product implementation of natural gradient and Herault-Jutten ICA update rules demonstrates comparable performance to benchmark FastICA algorithm in ideal conditions and more robust performance in noisy and reverberant environment. Experiments demonstrate perceptually clear separation and precise localization over wide range of separation angles of two speech sources presented through speakers positioned at 1.5 m from the array on a conference room table. The presented ASIC leads to a extreme small form factor and low power consumption microsystem for source separation and localization required in applications like intelligent hearing aids and wireless distributed acoustic sensor arrays.

Optimal position of the transmitter coil for wireless power transfer to the implantable device.

The maximum deliverable power through inductive link to the implantable device is limited by the tissue exposure to the electromagnetic field radiation. By moving away the transmitter coil from the body, the maximum deliverable power is increased as the magnitude of the electrical field at the interface with the body is kept constant. We demonstrate that the optimal distance between the transmitter coil and the body is on the order of 1 cm when the current of the transmitter coil is limited to 1 A. We also confirm that the conditions on the optimal frequency of the power transmission and the topology of the transmission coil remain the same as if the coil was directly adjacent to the body.

Mixed-signal VLSI independent component analyzer for hearing aid applications.

We present a mixed-signal architecture for implementation of independent component analysis designed for the task of blind source separation of acoustic sources interfacing miniature microphone array. The matrix-vector multiplication is implemented through integration of switched current sources controlled by the pulse-width modulated signals. The proposed architecture implementing 3×3 static ICA in 0.5µm CMOS technology occupies chip area of 0.49 mm(2) with the power consumption of 80µW at 5 V supply voltage.

Metabolic rate monitoring and weight reduction/management.

Engineering research may provide tools to the individual as well as to the public in general, to effectively monitor wellness and health patterns, such as metabolic rate and weight control. Ketone bodies and acetone gas emissions in exhaled breath and skin, in particular, may be used as biomarkers of fatty acid metabolism and may be used in diet control. Two types of technologies, resistive chemosensors and chemomechanical actuators are outlined here as examples of such tools currently under development and of great promise.

Low-power high-resolution 32-channel neural recording system.

A design of low-power 32-channel neural recording system with on-chip high-resolution A/D converters is presented. A neural front-end including low-noise fully differential pre-amplifier, gain stage, and buffer consumes only 56 mu W. Two 13-bits extended counting A/D converters running at 512KHz sampling rate are integrated with 32 neural front-ends on a chip. The experimental prototype was designed in 0.6 microm CMOS process. With a 3.3V power supply, total power consumption of a chip is 22mW and the whole system occupies an area of 3mm x 3mm.

Wireless multichannel integrated potentiostat for distributed neurotransmitter sensing.

Sensing neurotransmitters is critical in studying neural pathways and neurological disorders. An integrated device is presented which incorporates a potentiostat and a power harvesting and telemetry module. The potentiostat features 16 channels with multiple scales from microamperes to picoamperes. The wireless module is able to harvest power through inductively coupled coils and uses the same link to transmit data to and from the potentiostat. An integrated prototype is fabricated in CMOS technology, and experimentally characterized. Test results show RF powering introduces noise levels of 0.42% and 0.18% on potentiostat current scales of 500pA and 4nA respectively. Real-time multi-channel acquisition of dopamine concentration in vitro is performed with carbon fiber sensors.

Wide-range, picoampere-sensitivity multichannel VLSI potentiostat for neurotransmitter sensing.

Neurotransmitter sensing is critical in studying nervous pathways and neurological disorders. A 16-channel current-measuring VLSI potentiostat with multiple ranges from picoamperes to microamperes is presented for electrochemical detection of electroactive neurotransmitters like dopamine, nitric oxide etc. The analog-to-digital converter design employs a current-mode, first-order single-bit delta-sigma modulator architecture with a two-stage, digitally reconfigurable oversampling ratio for ranging the conversion scale. An integrated prototype is fabricated in CMOS technology, and experimentally characterized. Real-time multi-channel acquisition of dopamine concentration in vitro is performed with a microfabricated sensor array.