Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

The papers in this special section were presented at the 2020 International Symposium on Integrated Circuits and Systems (ISICAS) in a virtual conference that was held from August 27–28, 2020.

Bowel sounds (BSs), typically generated by the intestinal peristalses, are a significant physiological indicator of the digestive system's health condition. In this study, a wearable BS monitoring system is presented for long-term BS monitoring. The system features a wearable BS sensor that can record BSs for days long and transmit them wirelessly in real-time. With the system, a total of 20 subjects'

Recent review papers have investigated seizure prediction, creating the possibility of preempting epileptic seizures. Correct seizure prediction can significantly improve the standard of living for the majority of epileptic patients, as the unpredictability of seizures is a major concern for them. Today, the development of algorithms, particularly in the field of machine learning, enables reliable

This paper presents the noise optimization of a novel switched-capacitor (SC) based neural interface architecture, and its circuit demonstration in a 0.13 $\mu\text{m}$ CMOS process. To reduce thermal noise folding ratio, and suppress $kT/C$ noise, several noise optimization techniques are developed in the proposed architecture. First, one parasitic capacitance suppression scheme is developed to block

Biological nonassociative learning is one of the simplest forms of unsupervised learning in animals and can be categorized into habituation and sensitization according to mechanism. This paper proposes a memristive circuit that is based on nonassociative learning and can adapt to repeated inputs, reduce power consumption (habituation), and be sensitive to harmful inputs (sensitization). The circuit

A digital microfluidic biochip (DMB) is an attractive platform for automating laboratory procedures in microbiology. To overcome the problem of cross-contamination due to fouling of the electrode surface in traditional DMBs, a contactless liquid-handling biochip technology, referred to as acoustofluidics, has recently been proposed. A major challenge in operating this platform is the need for a control

Chronic in-vivo neurophysiology experiments require highly miniaturized, remotely powered multi-channel neural interfaces which are currently lacking in power or flexibility post implantation. In this article, to resolve this problem we present the SenseBack system, a post-implantation reprogrammable wireless 32-channel bidirectional neural interfacing that can enable chronic peripheral electrophysiology

In response to anticipated shortages of ventilators caused by the COVID-19 pandemic, many organizations have designed low-cost emergency ventilators. Many of these devices are pressure-cycled pneumatic ventilators, which are easy to produce but often do not include the sensing or alarm features found on commercial ventilators. This work reports a low-cost, easy-to-produce electronic sensor and alarm

A wideband wearable electromagnetic (EM) head imaging system for brain stroke detection is presented. The proposed system aims at overcoming the challenges of size, rigidity, and complex structures of existing systems. The proposed system is built into a light-weight and compact imaging platform, which integrates a 16-element antenna array into a highly flexible custom-made wearable cap made of a cost-effective

In this paper, we demonstrate a novel non-invasive, wearable impedance sensor. The impedance sensor, using an impedance to frequency measurement, with two modes of resistance and capacitance measurement is implemented in CMOS 130 nm technology. The sensor consisting of current and voltage comparators for different mode of measurement, has a low power consumption of 30 $ \mu$ W per channel. The sensor

Body bio-impedance is a unique parameter to monitor changes in body composition non-invasively. Continuous measurement of bio-impedance can track changes in body fluid content and cell mass and has widespread applications for physiological monitoring. State-of-the-art implementation of bio-impedance sensor devices is still limited for continuous use, in part, due to artefacts arising at the skin-electrode

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Advertisement.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

This page or pages intentionally left blank.

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

The eleven papers in this special section were presented at the 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS) in Nara, Japan, from October 17–19, 2019. Similar to previous years, BioCAS 2019 was jointly sponsored by the IEEE Circuits and Systems (CAS) Society and the IEEE Engineering in Medicine and Biology (EMB) Society.

This paper presents a device for time-gated fluorescence imaging in the deep brain, consisting of two on-chip laser diodes and 512 single-photon avalanche diodes (SPADs). The edge-emitting laser diodes deliver fluorescence excitation above the SPAD array, parallel to the imager. In the time domain, laser diode illumination is pulsed and the SPAD is time-gated, allowing a fluorescence excitation rejection

We propose a new paradigm of a smart wireless endoscopic capsule (WCE) that has the ability to select suspicious images containing a polyp before sending them outside the body. To do so, we have designed an image processing system to select images with Regions Of Interest (ROI) containing a polyp. The criterion used to select an ROI is based on the polyp's shape. We use the Hough Transform (HT), a

For mm-sized implants incorporating silicon integrated circuits, ensuring lifetime operation of the chip within the corrosive environment of the body still remains a critical challenge. For the chip's packaging, various polymeric and thin ceramic coatings have been reported, demonstrating high biocompatibility and barrier properties. Yet, for the evaluation of the packaging and lifetime prediction

Thermographic imaging accompanied with time-resolved analysis is a promising technique for intraoperative imaging in neurosurgery. However, motion due to breathing and pulse of the patient introduces large inaccuracies to the demarcation of normal and pathological brain tissue. Since movements and physiological processes are both manifested as temperature variations, we employ co-registered visual-light

With the increasing development of internet, the security of personal information becomes more and more important. Thus, variety of personal recognition methods have been introduced to ensure persons’ information security. Traditional recognition methods such as Personal Identification Number (PIN), or Identification tag (ID) are vulnerable to hackers. Then the biometric technology, which uses the

Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique decision trees to enable resource-efficient classification on a neural implant. By integrating model compression with probabilistic routing and implementing

Energy-constrained biomedical recording systems need power-efficient data converters and good signal compression in order to meet the stringent power consumption requirements of many applications. In literature today, typically a SAR ADC in combination with digital compression is used. Recently, alternative event-driven sampling techniques have been proposed that incorporate compression in the ADC

In this article, a novel method for measuring the volume of the urinary bladder non-invasively is presented that relies on the principles dictated by Electrical Impedance Tomography (EIT). The electronic prototype responsible for injecting innocuous electrical currents to the lower abdominal region and measuring the developed voltage levels is fully described, as well as the computational models for

Chronic neurological disorders (CND's) are lifelong diseases and cannot be eradicated, but their severe effects can be alleviated by early preemptive measures. CND's, such as Alzheimer's, Autism Spectrum Disorder (ASD), and Amyotrophic Lateral Sclerosis (ALS), are the chronic ailment of the central nervous system that causes the degradation of emotional and cognitive abilities. Long term continuous

Currently, the confirmation of diagnosis of breast cancer is made by microscopic examination of an ultra-thin slice of a needle biopsy specimen. This slice is conventionally formalin-fixed and stained with hematoxylin-eosin and visually examined under a light microscope. This process is labor-intensive and requires highly skilled doctors (pathologists). In this paper, we report a novel tool based on

We have developed a 5-electrode recording system that combines an implantable electromyography (EMG) device package with transcutaneous inductive power transmission, near-infrared (NIR) transcutaneous data telemetry and 3 Mbps Wi-Fi data acquisition for chronic EMG recording in vivo . This system comprises a hermetically-sealed single-chip, 5-electrode Implantable EMG Acquisition Device (IEAD), a custom

Electrochemical micro-sensors made of nano-graphitic (NG) carbon materials could offer high sensitivity and support voltammetry measurements at vastly different temporal resolutions. Here, we implement a configurable CMOS biochip for measuring low concentrations of bio-analytes by leveraging these advantageous features of NG micro-sensors. In particular, the core of the biochip is a discrete-time $\Delta

This paper presents a novel approach to design compact wearable antennas based on metasurfaces. The behavior of compact metasurfaces is modeled with a composite right-left handed transmission line (CRLH TL). By controlling the dispersion curve, the resonant modes of the compact metasurface can be tuned efficiently. A printed coplanar waveguide (CPW) monopole antenna is used as the feed structure to

Advertisement.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

This page or pages intentionally left blank.

Objective: The purpose of this paper is to demonstrate the use of 2-D impedance spectroscopy to identify areas of biofilm growth on a CMOS biosensor microelectrode-array. Methods: This paper presents the design and use of a novel multichannel impedance spectroscopy instrument to allow 2-D spatial and temporal evaluation of biofilm growth. The custom-designed circuits can provide a wide range of frequencies

Bioimpedance analysis is a noninvasive and inexpensive technology used to investigate the electrical properties of biological tissues. The analysis requires demodulation to extract the real and imaginary parts of the impedance. Conventional systems use complex architectures such as I-Q demodulation. In this paper, a very simple alternative time-to-digital demodulation method or ‘time stamp’ is proposed

To improve the SpO $_2$ sensing system performance for hypoperfusion (low perfusion index) applications, this paper proposes a low-noise light-to-frequency converter scheme from two aspects. First, a low-noise photocurrent buffer is proposed by reducing the amplifier noise floor with a transconductance-boost ( $g_{m}$ -boost) circuit structure. Second, a digital processing unit of pulse-frequency-duty-cycle

Sensing implants that can be deployed by catheterization or by injection are preferable over implants requiring invasive surgery. However, present powering methods for active implants and present interrogation methods for passive implants require bulky parts within the implants that hinder the development of such minimally invasive devices. In this article, we propose a novel approach that potentially

There is an unmet need for a low-cost instrumented technology for detecting sanitation-related malodor as an alert for maintenance around shared toilets and emerging technologies for onsite waste treatment. In this article, our approach to an electronic nose for sanitation-related malodor is based on the use of electrochemical gas sensors, and machine-learning techniques for sensor selection and odor

In the past few years it has been demonstrated that electroencephalography (EEG) can be recorded from inside the ear (in-ear EEG). To open the door to low-profile earpieces as wearable brain-computer interfaces (BCIs), this work presents a practical in-ear EEG device based on multiple dry electrodes, a user-generic design, and a lightweight wireless interface for streaming data and device programming

Research on heart rate (HR) estimation using wrist-worn photoplethysmography (PPG) sensors have progressed rapidly owing to the prominence of commercial sensing modules, used widely for lifestyle monitoring. Reported methodologies have been fairly successful in mitigating the effect of motion artifacts (MA) in ambulatory environment for HR estimation. Recently, a learning framework, CorNET, employing

This paper presents a low power, high dynamic range (DR), reconfigurable light-to-digital converter (LDC) for photoplethysmogram (PPG), and near-infrared spectroscopy (NIRS) sensor readouts. The proposed LDC utilizes a current integration and a charge counting operation to directly convert the photocurrent to a digital code, reducing the noise contributors in the system. This LDC consists of a latched

In this work, a dual-mode stimulus chip with a built-in high voltage generator was proposed to offer a broad-range current or voltage stimulus patterns for biomedical applications. With an on-chip and built-in high voltage generator, this stimulus chip could generate the required high voltage supply without additional supply voltage. With a nearly 20 V operating voltage, the overstress and reliability

Magnetomyography (MMG) with superconducting quantum interference devices (SQUIDs) enabled the measurement of very weak magnetic fields (femto to pico Tesla) generated from the human skeletal muscles during contraction. However, SQUIDs are bulky, costly, and require working in a temperature-controlled environment, limiting wide-spread clinical use. We introduce a low-profile magnetoelectric (ME) sensor

In this article, we present a real-time electroencephalogram (EEG) based depth of anesthesia (DoA) monitoring system in conjunction with a deep learning framework, AnesNET. An EEG analog front-end (AFE) that can compensate ±380-mV electrode DC offset using a coarse digital DC servo loop is implemented in the proposed system. The EEG-based MAC, EEGMAC, is introduced as a novel index to accurately predict

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Advertisement.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

This page or pages intentionally left blank.

Photoacoustic imaging (PAI), an emerging imaging technique, exploits the merits of both optical and ultrasound imaging, equipped with optical contrast and deep penetration. Typical linear PAI relies on a nanosecond laser pulse to induce photoacoustic signals. To construct a multi-wavelength PAI system, a multi-wavelength nano-second laser source is required, which greatly increases the cost of the

Neurons are the primary building block of the nervous system. Exploring the mysteries of the brain in science or building a novel brain-inspired hardware substrate in engineering are inseparable from constructing an efficient biological neuron. Balancing the functional capability and the implementation cost of a neuron is a grand challenge in neuromorphic field. In this paper, we present a low-cost

Continuous and robust monitoring of physiological signals is essential in improving the diagnosis and management of cardiovascular and respiratory diseases. The state-of-the-art systems for monitoring vital signs such as heart rate, heart rate variability, respiration rate, and other hemodynamic and respiratory parameters use often bulky and obtrusive systems or depend on wearables with limited sensing

This paper proposes novel methods for making embryonic bio-inspired hardware efficient against faults through self-healing, fault prediction, and fault-prediction assisted self-healing. The proposed self-healing recovers a faulty embryonic cell through innovative usage of healthy cells. Through experimentations, it is observed that self-healing is effective, but it takes a considerable amount of time

This paper presents an 8-channel energy-efficient analog front-end (AFE) for neural recording, with improvements in power supply rejection ratio (PSRR) and dynamic range. The input stage in the low noise amplifier (LNA) adopts low voltage supply (0.35 V) and current-reusing to achieve ultralow power. To maintain a high PSRR performance while using such a low-voltage supply, a replica-biasing scheme

An ASIC for a high frequency electrical impedance tomography (EIT) imaging system for prostate cancer screening is presented. The ASIC enables a small form-factor architecture, which ensures high signal-to-noise ratio (SNR) at MHz frequencies. The 4-channel ASIC was designed and fabricated in a standard CMOS 0.18- $\mu$ m technology and integrates a novel current driver for current stimulus, instrumentation

Presents the table of contents for this issue of the publication.