An Energy-Efficient CMOS Dual-Mode Array Architecture for High-Density ECoG-Based Brain-Machine Interfaces
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 the feature weights in the digital back-end during full-band mode operation. Subsequently, these weights are fed back to the front-end and the system reverts to base-band mode to perform feature extraction. This appro...
Source: IEEE Transactions on Biomedical Circuits and Systems - April 1, 2020 Category: Biomedical Engineering Source Type: research

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Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

A VLSI Implementation of Independent Component Analysis for Biomedical Signal Separation Using CORDIC Engine
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 the coordinate rotation digital computer (CORDIC) algorithm to calculate the hyperbolic functions $sinh(theta)$ and $cosh(theta)$ with the rotation of the hyperbolic coordinate system. Also, the rotation of the linear coordi...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

A 128 × 128 Current-Mode Ultra-High Frame Rate ISFET Array With In-Pixel Calibration for Real-Time Ion Imaging
An ultra-high frame rate and high spatial resolution ion-sensing Lab-on-Chip platform using a 128 × 128 CMOS ISFET array 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 non-idealities such as offset, trapped charge and drift by periodically resetting the floating gate of the ISFET sensor. Current mode row-parallel signal processing is applied throughout the readout pipeline including auto-zeroing circuits for the removal...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

Biointegrated and Wirelessly Powered Implantable Brain Devices: A Review
This article reviews biocompatibility and design approaches for developing biointegrated and wirelessly powered implantable neural devices in animals aimed at long-term neural interfacing and outlines current challenges toward developing the next generation of implantable neural devices. (Source: IEEE Transactions on Biomedical Circuits and Systems)
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

A 0.0023 mm$^2$/ch. Delta-Encoded, Time-Division Multiplexed Mixed-Signal ECoG Recording Architecture With Stimulus Artifact Suppression
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 of the digital feedback architecture is leveraged to time-division multiplex 64 differential input channels onto a shared mixed-signal front-end, reducing channel area by 2x compared to the state-of-the-art. The feedback DAC u...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

Flexible Body-Conformal Ultrasound Patches for Image-Guided Neuromodulation
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 for low intensity focused ultrasound neuromodulation at a resonance frequency of 1.3 MHz. Full-wave simulations were used to model the flexible arrays and estimate their generated pressure profiles. A focal depth o...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

An Integrated Multi-Channel Biopotential Recording Analog Front-End IC With Area-Efficient Driven-Right-Leg Circuit
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 senses the common-mode at the CCIA output so that the AFE gain is reused as the DRL loop gain. Therefore, area efficient unit-gain buffer with small averaging capacitors can be used in DRL circuit to reduce the circuit area ...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

The Role and Challenges of Body Channel Communication in Wearable Flexible Electronics
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 converter (ADC), a micro-controller unit (MCU), a radio, a power management unit (PMU), where the radio is the design bottleneck due to its high power consumption. Different from conventional wireless communications, ...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

Application of Deep Compression Technique in Spiking Neural Network Chip
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 the chip as well as the power consumption of the chip. This design achieves throughput per unit area of 1.1 GSOP/($text{s}!cdot!text{mm}^2$) at 1.2 V, and energy consumed per SOP of 35 pJ. A 2-layer fully-connected spiki...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

Kalman-Based Real-Time Functional Decomposition for the Spectral Calibration in Swept Source Optical Coherence Tomography
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 algorithm uses the Kalman approach to estimate the wavenumber index parameter $k$ from the Mach-Zender Interferometer signal which is then applied to an adaptive level crossing sampler to generate a sampling clock that $k$-linea...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

Robust Real-Time Embedded EMG Recognition Framework Using Temporal Convolutional Networks on a Multicore IoT Processor
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 reliable gesture controller design. In this paper, we present a complete wearable-class embedded system for robust sEMG-based gesture recognition, based on Temporal Convolutional Networks (TCNs). Firstly, we developed a novel ...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

A Fully Embedded Adaptive Real-Time Hand Gesture Classifier Leveraging HD-sEMG and Deep Learning
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 circuit board (PCB) to allow wrapping around the forearm. The sensor provides a low-noise digitization interface with wireless data transmission through an industrial, scientific and medical (ISM) radio link. An original frequ...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

Accurate, Very Low Computational Complexity Spike Sorting Using Unsupervised Matched Subspace Learning
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 power budget, the dictionary contains arrays of {–1, 0 and 1} and the algorithm need only process addition and subtraction operations. Three types of such dictionary were considered. To quantify and compare the performance...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

Deep Learning Approach for Epileptic Focus Localization
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 recordings. In this paper, we propose two methods based on deep learning targeting accurate automatic epileptic focus localization using the non-stationary EEG recordings. Our first proposed method is based on semi-supervised lea...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

ECG Authentication Hardware Design With Low-Power Signal Processing and Neural Network Optimization With Low Precision and Structured Compression
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, we present an accurate low-power device authentication system that employs electrocardiogram (ECG) signals as the biometric modality. The proposed ECG processor consists of front-end signal processing of ECG signals and back-end ...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

A 13.34 μW Event-Driven Patient-Specific ANN Cardiac Arrhythmia Classifier for Wearable ECG Sensors
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 implementation. Firstly, continuous-in-time discrete-in-amplitude (CTDA) signal flow is adopted to reduce the multiplication operations. Secondly, conditional grouping scheme (CGS) in combination with biased training (BT) is pro...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

The Design of Memristive Circuit for Affective Multi-Associative Learning
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 neuron will be activated and output pulses if its input exceeds the threshold. After it is activated, memristive neuron can automatically return to the inactive state. Memristive synapse can realize learning and forgetting...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

Who is the Winner? Memristive-CMOS Hybrid Modules: CNN-LSTM Versus HTM
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 (LSTM) can be a good alternative for implementing the hierarchy, modularity and sparsity of information processing. To demonstrate this, we draw a comparison of CNN-LSTM and HTM performance on a face recognition problem with a s...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

A Review of Algorithm & Hardware Design for AI-Based Biomedical Applications
This paper reviews the state of the arts and trends of the AI-Based biomedical processing algorithms and hardware. The algorithms and hardware 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 propagation neural network (BPNN), convolutional neural networks (CNN), probabilistic neural networks (PNN), recurrent neural networks (RNN), Short-term Memory Network (LSTM), fuzzy neural network and etc. The pros and cons of the ...
Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

Guest Editorial: Special Section on AI-Based Biomedical Circuits and Systems
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Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

IEEE Transactions on Biomedical Circuits and Systems
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Source: IEEE Transactions on Biomedical Circuits and Systems - March 31, 2020 Category: Biomedical Engineering Source Type: research

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An Energy-Quality Scalable STDP Based Sparse Coding Processor With On-Chip Learning Capability
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 techniques as following: First, the complex WTA operation is simplified based on the prediction of spike emitting neurons. Sparsity based approximation in spatial and temporal domain are also efficiently exploited to remove the...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

A 2.4 GHz ISM Band OOK Transceiver With High Energy Efficiency for Biomedical Implantable Applications
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 circuit, a current-reused self-mixing voltage controlled oscillator, and a quadruple-transconductance power amplifier. Numerous proposed techniques implemented in the mentioned circuits improve the energy per ...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

Modelling Dynamically Re-Sizeable Electrodes (DRE) for Targeted Transcutaneous Measurements in Impedance Plethysmography
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 easily affected by the placement of the electrodes relative to the targeted vasculature. This paper presents a novel method to adjust the active surface of electrodes, introducing Dynamically Re-sizeable Electrodes (DRE), to ...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

Chip-Scale Angle-Selective Imager for In Vivo Microscopic Cancer Detection
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 amplifier pixel using a custom 11fF MOM capacitor, achieving $text{8.2};text{V s}^{-1} text{pW}^{-1}$ sensitivity. The pixel includes a leakage current minimization circuit to remove signal-dependent reset switch leakage and...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

Highly Linear Phase-Canceling Self-Injection-Locked Ultrasonic Radar for Non-Contact Monitoring of Respiration and Heartbeat
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 signal, and this tunable delay serves as the radar output, which is linearly proportional to the displacement of the target. Without assuming weak injection, the frequency and phase equations for an SIL oscillator are derived...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

FPGA-Accelerated 3rd Generation DNA Sequencing
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 towards addressing this issue, the design and implementation of a low-power real-time FPGA hardware accelerator for the basecalling task of nanopore-based DNA measurements. Key basecalling computations are identified and p...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

A 2.64-$mu mathrm{W}$ 71-dB SNDR Discrete-Time Signal-Folding Amplifier for Reducing ADC's Resolution Requirement in Wearable ECG Acquisition Systems
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 need of gain-control circuitry while the high gain helps relax the resolution requirement of the analog-to-digital converter (ADC) that follows, thus resulting in lower power consumption and design complexity for the ADC. Fabr...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

CORDIC-Astrocyte: Tripartite Glutamate-IP3-Ca$^{2+}$ Interaction Dynamics on FPGA
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 to emulate a biological-plausible astrocyte and glutamate-release mechanism. The nonlinear terms of these models were calculated using a high-precision and cost-effective algorithm. Subsequently, the modified models were sim...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

An Integrated Biosensor System With a High-Density Microelectrode Array for Real-Time Electrochemical Imaging
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 a custom CMOS microchip. The microchip holds a 3.6 mm × 3.6 mm sensing area containing 16,064 Pt MEA, the associated 16,064 integrated read channels, and digital control circuits. The novel three-electrode system g...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

Current/Voltage Dual-Mode Single-Wire Simultaneous Bidirectional Interface Architecture for Sensor System
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 were implemented in a 65 nm CMOS technology for the sensor IC and the SoC, and they were designed for transmission rates of 1 Mb/s and 250 Kb/s, core areas of 0.008 mm2 and 0.142 mm2, and power consumptions of 7.1 μW and 145....
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

A Label-Free, Non-Intrusive, and Rapid Monitoring of Bacterial Growth on Solid Medium Using Microwave Biosensor
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 frequencies for differential operation. The transmission coefficient (S21) of the sensor is considered as the sensor's response with a designed and measured quality factor above 200 to ensure a high-resolution operation of...
Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

Editorial
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IEEE Transactions on Biomedical Circuits and Systems
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Source: IEEE Transactions on Biomedical Circuits and Systems - February 1, 2020 Category: Biomedical Engineering Source Type: research

Table of Contents
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2019 Index IEEE Transactions on Biomedical Circuits and Systems Vol. 13
This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries d...
Source: IEEE Transactions on Biomedical Circuits and Systems - December 1, 2019 Category: Biomedical Engineering Source Type: research

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Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication. (Source: IEEE Transactions on Biomedical Circuits and Systems)
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