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The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) algorithms to healthcare and biomedical applications at the edge. This can facilitate the advancement of medical Internet of Things (IoT) systems and Point of Care (PoC) devices. In this paper, we provide a tutorial describing how

In neurostimulation, wireless power transfer is an efficient technology to overcome several limitations affecting medical devices currently used in clinical practice. Several methods were developed over the years for wireless power transfer. In this review article, we report and discuss the three most relevant methodologies for extremely miniaturised implantable neurostimulators: ultrasound coupling

The eight papers in this special section were presented at the IEEE International Solid-State Circuits Conference (ISSCC)that was held in San Francisco, California, from February 16 to February 20, 2020.

This paper reports on a low-power readout IC (ROIC) for high-fidelity recording of the photoplethysmogram (PPG) signal. The system comprises a highly reconfigurable, continuous-time, second-order, incremental delta-sigma modulator (I–ΔΣM) as a light-to-digital converter (LDC), a 2-channel 10b light-emitting diode (LED) driver, and an integrated digital signal processing (DSP) unit. The LDC operation

This paper presents a reconfigurable, dual-output, regulating rectifier featuring pulse width modulation (PWM) and dual-mode pulse frequency modulation (PFM) control schemes for single-stage ac-to-dc conversion to provide two independently regulated supply voltages (each in 1.5–3 V) from an input ac voltage. The dual-mode PFM controllers feature event-driven regulation as well as frequency division

A wireless and battery-less trimodal neural interface system-on-chip (SoC), capable of 16-ch neural recording, 8-ch electrical stimulation, and 16-ch optical stimulation, all integrated on a 5 × 3 mm 2 chip fabricated in 0.35-μm standard CMOS process. The trimodal SoC is designed to be inductively powered and communicated. The downlink data telemetry utilizes on–off keying pulse-position modulation

This paper presents a millimeter-scale crystal-less wireless transceiver for volume-constrained insertable pills. Operating in the 402–405 MHz medical implant communication service (MICS) band, the phase-tracking receiver-based over-the-air carrier recovery has a ±160 ppm coverage. A fully integrated adaptive antenna impedance matching solution is proposed to calibrate the antenna impedance variation

A 1225-Channel Neuromorphic Retinal Prosthesis (RP) SoC is presented. Existing RP SoCs directly convert light intensity to electrical stimulus, which limit the adoption of delicate stimulus patterns to increase visual acuity. Moreover, a conventional centralized image processor leads to the local hot spot that poses a risk to the nearby retinal cells. To solve these issues, the proposed SoC adopts

This paper presents the first wireless and programmable neural stimulator leveraging magnetoelectric (ME) effects for power and data transfer. Thanks to low tissue absorption, low misalignment sensitivity and high power transfer efficiency, the ME effect enables safe delivery of high power levels (a few milliwatts) at low resonant frequencies ( $\sim$ 250 kHz) to mm-sized implants deep inside the body

This paper presents a wearable active concentric electrode for concurrent EEG monitoring and Body-Coupled Communication (BCC) data transmission. A three-layer concentric electrode eliminates the usage of wires. A common mode averaging unit (CMAU) is proposed to cancel not only the continuous common-mode interference (CMI) but also the instantaneous CMI of up to 51V pp . The localized potential matching

This paper presents the body-coupled power transmission and ambient energy harvesting ICs. The ICs utilize human body-coupling to deliver power to the entire body, and at the same time, harvest energy from ambient EM waves coupled through the body. The ICs improve the recovered power level by adapting to the varying skin-electrode interface parasitic impedance at both the TX and RX. To maximize the

Ultrasonic backscatter communication has gained popularity in recent years with the advent of deep-tissue sub-mm scale biosensing implants in which piezoceramic (piezo) resonators are used as acoustic antennas. Miniaturization is a key design goal for such implants to reduce tissue displacement and enable minimally invasive implantation techniques. Here, we provide a systematic design approach for

In recent years, electroceuticals have been spotlighted as an emerging treatment for various severe chronic brain diseases, owing to their intrinsic advantage of electrical interaction with the brain, which is the most electrically active organ. However, the majority of research has verified only the short-term efficacy through acute studies in laboratory tests owing to the lack of a reliable miniaturized

Planar microwave sensors are considered an attractive choice to noninvasively probe the dielectric attributes of biological tissues due to their low cost, simple fabrication, miniature scale, and minimum risk to human health. This paper develops and measures a novel microwave biosensor for non-invasive real-time monitoring of glucose level. The design comprises a rectangular plexiglass channel integrated

A bio-potential recorder working under 0.8 V supply voltage with a tunable low-pass filter is proposed in this paper. The prototype is implemented in TSMC 180 nm CMOS technology, featuring a power consumption of 2.27 $\mu$ W, while preserving a high tolerance of power-line interference (PLI) up to 600 m $V_{pp}$ , a common-mode rejection ratio (CMRR) of higher than 100 dB, a THD of −65.5 dB, and a

A flexible, multifunctional, and intelligent analgesic bracelet was proposed in this article to alleviate symptoms of pain. Based on the theory of wrist-ankle acupuncture in traditional Chinese medicine, transcutaneous electrical nerve stimulation is the technical basis of the method. A set of targeted circuit system capable of generating adjustable electrical stimulation signals to simulate filamentary

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Detection and counting of biological living cells in continuous fluidic flows play an essential role in many applications for early diagnosis and treatment of diseases. In this regard, this study highlighted the proposal of a biochip system for detecting and enumerating human lung carcinoma cell flow in the microfluidic channel. The principle of detection was based on the change of impedance between

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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

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This paper presents a pulse-stimulus sensor readout circuit for use in cardiovascular disease examinations. The sensor is based on a gold nanoparticle plate with an antibody post-modification. The proposed system utilizes gated pulses to detect the biomarker Cardiac Troponin I in an ionic solution. The characteristic of the electrostatic double-layer capacitor generated by the analyte is related to

Noninvasive monitoring is an important Internet-of-Things application, which is made possible with the advances in radio-frequency based detection technologies. Existing techniques however rely on the use of antenna array and/or frequency modulated continuous wave radar to detect vital signs of multiple adjacent objects. Antenna size and limited bandwidth greatly limit the applicability. In this paper

Photoplethysmographic (PPG) measurements from ambulatory subjects may suffer from unreliability due to body movements and missing data segments due to loosening of sensor. This paper describes an on-device reliability assessment from PPG measurements using a stack denoising autoencoder (SDAE) and multilayer perceptron neural network (MLPNN). The missing segments were predicted by a personalized convolutional

A single-chip Gaussian monocycle pulse (GMP) transceiver was developed for radar-based microwave imaging by the use of 65-nm complementary metal oxide semiconductor (CMOS) technology. A transmitter (TX) generates GMP signals, whose pulse widths and −3 dB bandwidths are 192 ps and 5.9 GHz, respectively. A 102.4 GS/s equivalent time sampling receiver (RX) performs the minimum jitter, input referred noise

The tracking of eye gesture movements using wearable technologies can undoubtedly improve quality of life for people with mobility and physical impairments by using spintronic sensors based on the tunnel magnetoresistance (TMR) effect in a human–machine interface. Our design involves integrating three TMR sensors on an eyeglass frame for detecting relative movement between the sensor and tiny magnets

The neuron behavioral models are inspired by the principle of the firing of neurons, and weighted accumulation of charge for a given set of input stimuli. Biological neurons show dynamic behavior through its feedback and feedforward time-dependent responses. The principle of the firing of neurons inspires threshold logic design by applying threshold functions on the weight summation of inputs. In this

This paper presents an energy-efficient mm-scale self-contained bidirectional optogenetic neuro-stimulator, which employs a novel highly-linear $\mu$ LED driving circuit architecture as well as inkjet-printed custom-designed optical $\mu$ lenses for light directivity enhancement. The proposed current-mode $\mu$ LED driver performs linear control of optical stimulation for the entire target range (

This article presents the design of an unobtrusive and wireless-enabled blood pressure (BP) monitoring system that is suitable for ambulatory use. By adopting low-profile electromechanical actuators and a compact printed circuit board design, this lightweight device can be worn directly on the occlusive cuff, therefore eliminating the need of a long and obtrusive tubing interconnect between the device

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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