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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 0.18μm technology and integrates a novel current driver for current stimulus, instrumentation

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The papers in this special section present a selection of research on artificial intelligence-based biomedical circuits and systems.

This paper reviews the state of the arts and trends of the AI-based biomedical processing algorithms and hardwares. The algorithms and hardwares for different biomedical applications such as ECG, EEG and hearing aid have been reviewed and discussed. For algorithm design, various widely used biomedical signal classification algorithms have been discussed including support vector machine (SVM), back

Hierarchical, modular and sparse information processing are signature characteristics of biological neural networks. These aspects have been the backbone of several artificial neural network designs of the brain-like networks, including Hierarchical Temporal Memory (HTM). The main contribution of this work is showing that Convolutional Neural Network (CNN) in combination with Long short term memory

In this work, a memristive circuit with affective multi-associative learning function is proposed, which mimics the process of human affective formation. It mainly contains three modules: affective associative learning, affective formation, affective expression. The first module is composed of several affective single-associative learning circuits consisting of memristive neurons and synapses. Memristive

Artificial neural network (ANN) and its variants are favored algorithm in designing cardiac arrhythmia classifier (CAC) for its high accuracy. However, the implementation of ultralow power ANN-CAC is challenging due to the intensive computations. Moreover, the imbalanced MIT-BIH database limits the ANN-CAC performance. Several novel techniques are proposed to address the challenges in the low power

Biometrics such as facial features, fingerprint, and iris are being used increasingly in modern authentication systems. These methods are now popular and have found their way into many portable electronics such as smartphones, tablets, and laptops. Furthermore, the use of biometrics enables secure access to private medical data, now collected in wearable devices such as smartwatches. In this work,

The task of epileptic focus localization receives great attention due to its role in an effective epileptic surgery. The clinicians highly depend on the intracranial EEG data to make a surgical decision related to epileptic subjects suffering from uncontrollable seizures. This surgery usually aims to remove the epileptogenic region which requires precise characterization of that area using the EEG

This paper presents an adaptable dictionary-based feature extraction approach for spike sorting offering high accuracy and low computational complexity for implantable applications. It extracts and learns identifiable features from evolving subspaces through matched unsupervised subspace filtering. To provide compatibility with the strict constraints in implantable devices such as the chip area and

This paper presents a real-time fine gesture recognition system for multi-articulating hand prosthesis control, using an embedded convolutional neural network (CNN) to classify hand-muscle contractions sensed at the forearm. The sensor consists in a custom non-intrusive, compact, and easy-to-install 32-channel high-density surface electromyography (HDsEMG) electrode array, built on a flexible printed

Hand movement classification via surface electromyographic (sEMG) signal is a well-established approach for advanced Human-Computer Interaction. However, sEMG movement recognition has to deal with the long-term reliability of sEMG-based control, limited by the variability affecting the sEMG signal. Embedded solutions are affected by a recognition accuracy drop over time that makes them unsuitable for

This paper presents a real-time functional decomposition adaptive algorithm for the optimal sampling of the interferometric signal in Swept-Source Optical Coherence Tomography imaging systems, which completely eliminates the input signal dependent nonlinearities that are problematic in current state-of-the-art OCT realizations that use interpolation and resampling. The proposed adaptive calibration

In this paper, a reconfigurable and scalable spiking neural network processor, containing 192 neurons and 6144 synapses, is developed. By using deep compression technique in spiking neural network chip, the amount of physical synapses can be reduced to 1/16 of that needed in the original network, while the accuracy is maintained. This compression technique can greatly reduce the number of SRAMs inside

Flexible electronics are compatible with film substrates that are soft and stretchable, resulting in conformal integration with human body. Integrated with various sensors and communication ICs, wearable flexible electronics are able to effectively track human vital signs without affecting the body activities. Such a wearable flexible system contains a sensor, a front-end amplifier (FEA), an analog-to-digital

A multi-channel biopotential recording analog front-end (AFE) with a fully integrated area-efficient driven-right-leg (DRL) circuit is presented in this paper. The proposed AFE includes 10 channels of low-noise capacitive coupled instrumentation amplifier (CCIA), one shared 10-bit SAR ADC and a fully integrated DRL to enhance the system-level common-mode rejection ratio (CMRR). The proposed DRL circuit

The paper presents the design and validation of body-conformal active ultrasound patches with integrated imaging and modulation modalities for image-guided neural therapy. A mechanically-flexible linear 64-element array of piezoelectric transducers with a resonance frequency of 5 MHz was designed for nerve localization. A second 8-element array using larger elements was integrated on the wearable probe

This article demonstrates a scalable, time-division multiplexed biopotential recording front-end capable of real-time differential- and common-mode artifact suppression. A delta-encoded recording architecture exploits the power spectral density (PSD) characteristics of Electrocorticography (ECoG) recordings, combining an 8-bit ADC, and an 8-bit DAC to achieve 14 bits of dynamic range. The flexibility

This article presents an energy-efficient electrocorticography (ECoG) array architecture for fully-implantable brain machine interface systems. A novel dual-mode analog signal processing method is introduced that extracts neural features from high- $\gamma$ band (80–160 Hz) at the early stages of signal acquisition. Initially, brain activity across the full-spectrum is momentarily observed to compute

Implantable neural interfacing devices have added significantly to neural engineering by introducing the low-frequency oscillations of small populations of neurons known as local field potential as well as high-frequency action potentials of individual neurons. Regardless of the astounding progression as of late, conventional neural modulating system is still incapable to achieve the desired chronic

An ultra-high frame rate and high resolution ion-sensing Lab-on-Chip platform using a 128x128 CMOS ISFETarray is presented. Current mode operation is employed to facilitate high-speed operation, with the ISFET sensors biased in the triode region to provide a linear response. Sensing pixels include a reset switch to allow in pixel-calibration for nonidealities such as offset, trapped charge and drift

This study aims to design and implement a very large scale integration (VLSI) chip of the extend InfoMax independent component analysis (ICA) algorithm which can separate the super-Gaussian source signals. In order to substantially reduce the circuit area, the proposed circuit utilizes the time sharing matrix multiplication array (MMA) to realize a series of matrix multiplication operations and employs

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It is essential but quite challenging to alleviate speech information loss and distortion while developing the speech processing algorithms in hearing aids. Recently, many speech enhancement methods based on deep learning are proven effective. However, most of the algorithms fail to achieve real-time processing, which is significant for hearing aids, especially for a smartphone-centered binaural hearing

Conventional cochlear implants using periodic sampling are power consuming and incapable of capturing the amplitude and phase of the input acoustic signal simultaneously. This paper presents an asynchronous event-driven encoder chip for cochlear implants capable of extracting the temporal fine structure. The chip architecture is based on asynchronous delta modulation (ADM) where the signal peak/trough

The irreversible electroporation with microsecond electric pulses is a new ablation technique adopted in the tumor therapy worldwide. On the other hand, the nsPEF (nanosecond pulsed electric field) has been proved to provide a means to induce immunogenic cell death and elicits antitumor immunity, which is under intensive in-vitro and in-vivo studies and in clinical trials. Normally, one needs two different

This paper presents a SAR converter based mixed-signal multiplier for the feature extraction of neural signals using quadratic operators. After a thorough analysis of design principles and circuit-level aspects, the proposed architecture is explored for the implementation of two quadratic operators often used for the characterization of neural activity, the moving average energy operator and the nonlinear

This paper presents an ultrasonically powered microsystem for deep tissue optogenetic stimulation. All the phases in developing the prototype starting from modelling the piezoelectric crystal used for energy harvesting, design, simulation and measurement of the chip, and finally testing the whole system in a mimicking setup are explained. The developed system is composed of a piezoelectric harvesting

Ultrasound (US) imaging systems typically employ a single beamforming scheme which is the delay and sum (DAS) beamforming due to its reduced complexity. However, DAS results in low-quality images due to limited resolution and noise rejection. The restrictions of DAS have been overcome by, delay multiply and sum (DMAS) beamforming, by providing better contrast and resolution than DAS, making it especially

This paper presents a 10-bit successive approximation analog-to-digital converter (ADC) that operates at an ultralow voltage of 0.3 V and can be applied to biomedical implants. The study proposes several techniques to improve the ADC performance. A pipeline comparator was utilized to maintain the advantages of dynamic comparators and reduce the kickback noise. Weight biasing calibration was used to

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Microwave resonator sensors are attractive for their contactless and label-free capability of monitoring bacterial growth in liquid media. This paper outlines a new label-free microwave biosensor based on a pair of planar split ring resonators for non-invasive monitoring of bacterial growth on a solid agar media. The sensor is comprised of two split ring resonators with slightly different resonant

This paper presents a simultaneous bidirectional asymmetrical serial interface architecture for sensor systems. The proposed current/voltage dual-mode signaling scheme provides system synchronous clock and continuous data transmission between sensor integrated circuit (IC) and system-on-a-chip (SoC) using a single wire, which minimizes pin requirements on packages. Two types of transceiver circuits

Electrochemical methods have been shown to be advantageous to life sciences by supporting studies and discoveries in metabolism activities, DNA analysis, and neurotransmitter signaling. Meanwhile, the integration of Microelectrode Array (MEA) and the accessibility of CMOS technology permit high-density electrochemical sensing method. This paper describes an electrochemical imaging system equipped with

Real-time, large-scale simulation of biological systems is challenging due to different types of nonlinear functions describing biochemical reactions in the cells. The promise of the high speed, cost effectiveness, and power efficiency in addition to parallel processing has made application-specific hardware an attractive simulation platform. This paper proposes high-speed and low-cost digital hardware

This paper presents the design of a low-power discrete-time signal-folding amplifier intended for use in place of programmable-gain amplifiers (PGA) in electrocardiogram (ECG) acquisition systems. The amplifier provides a fixed high gain while preventing output signal saturation even with rail-to-rail inputs, thanks to the proposed discrete-time signal folding technique; the fixed gain eliminates the

DNA measurement machines are undergoing an orders-of-magnitude size and power reduction. As a result, the analysis of genetic molecules is increasingly appropriate for mobile platforms. However, sequencing these measurements (converting to the molecule's A-C-G-T text equivalent) requires intense computing resources, a problem for potential realizations as mobile devices. This paper proposes a step

A novel phase-canceling demodulation scheme to improve the linearity of a self-injection-locked (SIL) ultrasonic radar is proposed with the goal of solving the null detection problem and accurately sensing large displacements of a moving target. A proportional-integral (PI) controller regulates the phase of the injection signal and cancels the Doppler phase shift by tuning a delay in the received echo

We present an image sensor incorporating angle-selective gratings for resolution enhancement in contact imaging applications. Optical structures designed in the CMOS metal layers above each photodiode form the angle-selective gratings that limit the sensor angle of view to $\pm$ 18 $^{\circ }$ , rejecting background light and deblurring the image. The imager is based on a high-gain capacitive transimpedance

Impedance plethysmography of extremities typically involves band electrodes around limbs to monitor changes in blood volume. This often causes monitored blood variations to only generate minuscule impedance values relative to the measured baseline, attributed to the tissue surrounding the artery or vein of interest. Smaller, ECG type electrodes can provide a larger signal, however their output is very

This article presents a high energy efficiency, high-integrated, and low-power on-off keying transceiver for a 2.4 GHz industrial scientific medical band. The proposed receiver includes an input matching network, a low-noise amplifier, a novel single-to-differential envelope detector, a level shifter, cascaded baseband amplifiers, and a hysteresis comparator. The proposed transmitter includes a bias-stimulating

Two main bottlenecks encountered when implementing energy-efficient spike-timing-dependent plasticity (STDP) based sparse coding, are the complex computation of winner-take-all (WTA) operation and repetitive neuronal operations in the time domain processing. In this article, we present an energy-efficient STDP based sparse coding processor. The low-cost hardware is based on the algorithmic reduction

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