A5089070385- Analog and Mixed-Signal Circuit Design
- Neuroscience and Neural Engineering
- Analytical Chemistry and Sensors
- Diamond and Carbon-based Materials Research
- EEG and Brain-Computer Interfaces
- Advancements in Semiconductor Devices and Circuit Design
- CCD and CMOS Imaging Sensors
- Electrical and Bioimpedance Tomography
- ECG Monitoring and Analysis
- Radio Frequency Integrated Circuit Design
- Semiconductor materials and devices
- Advanced Power Amplifier Design
- Non-Invasive Vital Sign Monitoring
- Sensor Technology and Measurement Systems
- Advanced Sensor and Energy Harvesting Materials
- Big Data and Business Intelligence
- Advanced DC-DC Converters
- Advanced Memory and Neural Computing
- Muscle activation and electromyography studies
- Metal and Thin Film Mechanics
- Advancements in PLL and VCO Technologies
- Ion-surface interactions and analysis
- Multilevel Inverters and Converters
- Advanced Electrical Measurement Techniques
- Low-power high-performance VLSI design
Fudan University
2018-2025
Jiangxi University of Traditional Chinese Medicine
2025
University of Electronic Science and Technology of China
2020-2024
Dalian Medical University
2024
Anhui University of Technology
2024
Anhui University
2023
Holst Centre (Netherlands)
2011-2021
Shanghai Fudan Microelectronics (China)
2018-2021
State Key Laboratory of ASIC and System
2018-2021
China Academy of Space Technology
2021
This paper presents an active electrode system for gel-free biopotential EEG signal acquisition. The consists of front-end chopper amplifiers and a back-end common-mode feedback (CMFB) circuit. AC-coupled amplifier employs input impedance boosting digitally-assisted offset trimming. former increases the to 2 GΩ at 1 Hz latter limits chopping induced output ripple residual mV 20 mV, respectively. Thanks stabilization, achieves 0.8 μVrms (0.5-100 Hz) referred noise. use CMFB circuit further...
<?Pub Dtl=""?> This paper describes an 8-channel gel-free EEG/electrode-tissue impedance (ETI) acquisition system, consisting of nine active electrodes (AEs) and one back-end (BE) analog signal processor. The AEs amplify the weak EEG signals, while their low output suppresses cable-motion artifacts 50/60 Hz mains interference. A common-mode feed-forward (CMFF) scheme boosts CMRR AE pairs by 25 dB. BE post-processes digitizes outputs AEs, it also can configure them via a single-wire pulse...
An all-in-one battery powered low-power SoC for measuring multiple vital signs with wearables is proposed. All functionality needed in a typical wearable use case scenario, including dedicated readouts, power management circuitry, digital signal processing and wireless communication (BLE) integrated single die. This high level of integration allows an unprecedented miniaturization leading to smaller component count which reduces cost improves comfort integrity. The includes ECG,...
This paper presents a digital active electrode (DAE) system for multi-parameter biopotential signal acquisition in portable and wearable devices. It is built around an IC that performs analog processing digitization with the help of on-chip instrumentation amplifiers, 12 bit ADC interface. Via standard <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${\rm I}^{{2}}{\rm C}$</tex> </formula> bus, up to...
This paper presents a theoretical analysis and measurements of the current noise several chopper instrumentation amplifiers, which demonstrate that charge injection clock feed-through associated with MOSFETs input give rise to significant noise. In combination high source impedances, this "chopper noise" is converted voltage noise, may then be contributor amplifier's total input-referred Chopper has white power spectral density, whose magnitude roughly proportional chopping frequency. Design...
This paper presents a sub-mW ASIC for multimodal brain monitoring. The is co-integrated with electrode(s) and optodes (i.e., optical source detector) as an active sensor to measure electroencephalography (EEG), bio-impedance (BioZ), near-infrared spectroscopy (NIRS) on scalp. target build wearable EEG-NIRS headset low-cost functional imaging. proposed NIRS readout utilizes the light pulse oximetry blood oxygen saturation (SpO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML"...
The measurement of the tissue or bio-impedance (BIOZ) is a safe and power-efficient sensing modality that can be adopted for acquisition vital signals, such as respiration heartbeat. A BIOZ readout IC with wide-input impedance range proposed. supports signal through two-electrode setup which requires larger dynamic than conventional four-electrode setup. digital-assisted baseline cancellation method implemented to measure small variations originating from heartbeat in presence impedances....
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 current integration charge counting operation to directly convert the photocurrent digital code, reducing noise contributors in system. consists of latched comparator, low-noise reference, counter, multi-function integrator, which is used both signal amplification based data...
Deep learning is a subset of machine that models data using artificial neural networks with multiple layers. Each layer in the network processes input data, extracts relevant features, and passes it to next layer. techniques have led significant advancements areas such as image recognition, natural language processing, speech recognition.
This paper presents a 1.2 V 36 μW reconfigurable analog front-end (R-AFE) as general-purpose low-cost IC for multiple-mode biomedical signals acquisition. The R-AFE efficiently reuses preamplifier, current generator (CG), and mixed signal processing unit, having an area of 1.1 mm2 per while supporting five acquisition modes to record different forms cardiovascular respiratory signals. can interface with voltage-, current-, impedance-, light-sensors hence measure electrocardiography (ECG),...
Non-invasive, closed-loop brain modulation offers an accessible and cost-effective means of evaluating modulating one's mental physical well-being, such as Parkinson's disease, epilepsy, sleep disorders. However, wearable EEG systems pose significant challenges for the analog front-end (AFE) circuits in view µV-level signals interest, multiple sources interference, ill-defined skin contact. This paper presents a direct-digitization AFE tailored dry-electrode scalp recording, characterized by...
An important drawback of current biopotential monitoring systems is their dependence on gel electrodes, which can dry out, cause skin irritation, and necessitate skilled personnel. These associated drawbacks increase the running costs significantly hamper use in consumer healthcare lifestyle applications. Unfortunately, gel-free, or dry, electrodes increases electrode-tissue contact impedance, thus exacerbating effects interference cable motion artifacts. A solution active i.e. an amplifier...
In this paper, we present a miniaturized (<6cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) and low noise (60nV/√Hz) wireless EEG sensor node with active electrodes simultaneous electrode tissue impedance (ETI) monitoring. The added benefit of the continuous ETI monitoring is quantified in terms susceptibility against power line interference cable motion artefacts. benchmarked reference system for similarity measures frequency...
Motion artifacts (MA), common-mode interference (CMI), and varying electrode-tissue impedance (ETI) are the main factors that cause heart rate detection errors in practical wearable ECG acquisition. These problems further exacerbated two-electrode based systems. This article presents an ambulatory acquisition ASIC with fully integrated, low power motion removal (MAR) detection, specifically for measurement. To alleviate significant CMI due to absence of subject bias electrode, this work...
This article presents a direct-digitization analog front end (DD-AFE) with enhanced input-impedance, common-mode rejection ratio (CMRR), and dynamic range (DR) for wearable biopotential (ExG) signal acquisition, especially small-diameter dry electrodes. The DD-AFE employs second-order continuous-time delta-sigma modulator (CT-ΔSM) multiple circuit techniques to support readouts. These include 1) A high input-impedance input feedforward (FF), embedded in 4-input 4-bit successive approximation...
The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable sophisticated reasoning, robust perception, and versatile action across diverse domains. As these increasingly drive AI research practical applications, their design, evaluation, continuous improvement present intricate, multifaceted challenges. This survey provides comprehensive overview, framing within modular, brain-inspired...
Background/Objective: Chimonanthus salicifolius S.Y.Hu ( C. ) is one of the most important herbs in She nationality China. For similar appearance and nitens Oliv. ), they are often used confusion folk. In order to preliminarily estimate whether pharmaceutical base source , this study, essential oil components from different locations China were analyzed for first time. Methods: The by gas chromatography coupled with mass spectrometry (GC-MS). Results: two oils contained 67 71 compounds,...
Large Language Models (LLMs) have become a cornerstone of modern artificial intelligence (AI), finding applications across various domains such as healthcare, finance, entertainment, and customer service. To understand their ethical social implications, it is essential to first grasp what these models are, how they function, why carry significant impact. This introduction aims provide comprehensive beginner-friendly overview LLMs, introducing basic structure, training process, the types...