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DC Field | Value | Language |
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dc.citation.endPage | 273 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 263 | - |
dc.citation.title | IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS | - |
dc.citation.volume | 18 | - |
dc.contributor.author | Wu, Jiajia | - |
dc.contributor.author | Akinin, Abraham | - |
dc.contributor.author | Somayajulu, Jonathan | - |
dc.contributor.author | Lee, Min S | - |
dc.contributor.author | Paul, Akshay | - |
dc.contributor.author | Lu, Hongyu | - |
dc.contributor.author | Park, Yongjae | - |
dc.contributor.author | Kim, Seong-Jin | - |
dc.contributor.author | Mercier, Patrick P | - |
dc.contributor.author | Cauwenberghs, Gert | - |
dc.date.accessioned | 2024-03-04T14:05:12Z | - |
dc.date.available | 2024-03-04T14:05:12Z | - |
dc.date.created | 2024-02-26 | - |
dc.date.issued | 2024-04 | - |
dc.description.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. | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, v.18, no.2, pp.263 - 273 | - |
dc.identifier.doi | 10.1109/TBCAS.2024.3368068 | - |
dc.identifier.issn | 1932-4545 | - |
dc.identifier.scopusid | 2-s2.0-85186991100 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/81514 | - |
dc.identifier.wosid | 001196728500016 | - |
dc.language | 영어 | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | A Low-Noise Low-Power 0.001Hz–1kHz Neural Recording System-on-Chip with Sample-Level Duty-Cycling | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Engineering, Biomedical;Engineering, Electrical & Electronic | - |
dc.relation.journalResearchArea | Engineering | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | biopotential recording | - |
dc.subject.keywordAuthor | delta-sigma ADC | - |
dc.subject.keywordAuthor | EEG | - |
dc.subject.keywordAuthor | EGG | - |
dc.subject.keywordAuthor | low-noise | - |
dc.subject.keywordAuthor | low-power | - |
dc.subject.keywordAuthor | Multichannel | - |
dc.subject.keywordAuthor | sample-level duty-cycling | - |
dc.subject.keywordAuthor | wideband | - |
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