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김성진

Kim, Seong-Jin
Bio-inspired Advanced Sensors Lab.
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A Low-Noise Low-Power 0.001Hz–1kHz Neural Recording System-on-Chip with Sample-Level Duty-Cycling

Author(s)
Wu, JiajiaAkinin, AbrahamSomayajulu, JonathanLee, Min SPaul, AkshayLu, HongyuPark, YongjaeKim, Seong-JinMercier, Patrick PCauwenberghs, Gert
Issued Date
2024-02
DOI
10.1109/TBCAS.2024.3368068
URI
https://scholarworks.unist.ac.kr/handle/201301/81514
Citation
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS
Abstract
Advances in brain-machine interfaces and wearable biomedical sensors for healthcare and human-computer interactions call for precision electrophysiology to resolve a variety of biopotential signals across the body that cover a wide range of frequencies, from the mHz-range electrogastrogram (EGG) to the kHz-range electroneurogram (ENG). Existing integrated wearable solutions for minimally invasive biopotential recordings are limited in detection range and accuracy due to trade-offs in bandwidth, noise, input impedance, and power consumption. This article presents a 16-channel wide-band ultra-low-noise neural recording system-on-chip (SoC) fabricated in 65nm CMOS for chronic use in mobile healthcare settings that spans a bandwidth of 0.001 Hz to 1 kHz through a featured sample-level duty-cycling (SLDC) mode. Each recording channel is implemented by a delta-sigma analog-to-digital converter (ADC) achieving 1.0 μ V rms input-referred noise over 1Hz–1kHz bandwidth with a Noise Efficiency Factor (NEF) of 2.93 in continuous operation mode. In SLDC mode, the power supply is duty-cycled while maintaining consistently low input-referred noise levels at ultra-low frequencies (1.1 μ V rms over 0.001Hz–1Hz) and 435 MΩ input impedance. The functionalities of the proposed SoC are validated with two human electrophysiology applications: recording low-amplitude electroencephalogram (EEG) through electrodes fixated on the forehead to monitor brain waves, and ultra-slow-wave electrogastrogram (EGG) through electrodes fixated on the abdomen to monitor digestion.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
ISSN
1932-4545

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