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An 8-channel 2.1 μ W0.017 mm2 0.04% Gain Mismatch Bio-potential Recording AFE using Group-Chopping Technique

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dc.contributor.authorTang, Tao-
dc.contributor.authorPark, Jeonghoan-
dc.contributor.authorZhang, Lian-
dc.contributor.authorNg, Kian Ann-
dc.contributor.authorYoo, Jerald-
dc.date.accessioned2024-05-03T04:33:04Z-
dc.date.available2024-05-03T04:33:04Z-
dc.date.created2024-05-02-
dc.date.issued2019-
dc.identifier.citationProceedings of the Custom Integrated Circuits Conference, Vol.2019-April-
dc.identifier.issn0886-5930-
dc.identifier.urihttps://hdl.handle.net/10371/200817-
dc.description.abstractAn 8-ch bin-potential recording AFE with less than 0.04% gain mismatch is presented. The proposed Group Chopping Instrumentation Amplifier (GCIA) exploits groupchopping scheme with 8 -phase non-overlapping clocks to achieve the lowest gain mismatch reported to date and improses between channel CMRR among all channels, while mitigating dynamic offsets at once. The proposed GCIA is the first in literature to mitigate gain mismatch for more than 2 channels. Fabricated in 0.18 mu m CMOS, it consumes 2.1 mu W/Ch. under 0.5V supply and achieves NEF of 2.1, sshile occupying 0.017 mm(2)/Ch.-
dc.language영어-
dc.publisherProceedings of the Custom Integrated Circuits Conference-
dc.titleAn 8-channel 2.1 μ W0.017 mm2 0.04% Gain Mismatch Bio-potential Recording AFE using Group-Chopping Technique-
dc.typeArticle-
dc.identifier.doi10.1109/CICC.2019.8780269-
dc.citation.journaltitleProceedings of the Custom Integrated Circuits Conference-
dc.identifier.wosid000501010700080-
dc.identifier.scopusid2-s2.0-85070551849-
dc.citation.volume2019-April-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorYoo, Jerald-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
dc.subject.keywordAuthorgroup chopping-
dc.subject.keywordAuthorbio-recording AFE-
dc.subject.keywordAuthorgain mismatch-
dc.subject.keywordAuthorbetween channel CAME (CMRRbtw-chn)-
dc.subject.keywordAuthormulti-channel gain mismatch mitigation-
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부교수
  • College of Engineering
  • Department of Electrical and Computer Engineering
Research Area Biomedical Applications, Energy-Efficient Integrated Circuits

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