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A 16-Channel Patient-Specific Seizure Onset and Termination Detection SoC With Impedance-Adaptive Transcranial Electrical Stimulator

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dc.contributor.authorBin Altaf, Muhammad Awais-
dc.contributor.authorZhang, Chen-
dc.contributor.authorYoo, Jerald-
dc.date.accessioned2024-05-03T04:34:01Z-
dc.date.available2024-05-03T04:34:01Z-
dc.date.created2024-05-02-
dc.date.issued2015-11-
dc.identifier.citationIEEE JOURNAL OF SOLID-STATE CIRCUITS, Vol.50 No.11, pp.2728-2740-
dc.identifier.issn0018-9200-
dc.identifier.urihttps://hdl.handle.net/10371/200832-
dc.description.abstractA 16-channel noninvasive closed-loop beginning-and end-of-seizure detection SoC is presented. The dual-channel charge recycled (DCCR) analog front end (AFE) achieves chopping and time-multiplexing an amplifier between two channels simultaneously which exploits fast-settling DC servo-loop with current consumption and NEF of 0.9 mu A/channel and 3.29/channel, respectively. The dual-detector architecture (D(2)A) classification processor utilizes two linear support-vector machine (LSVM) classifiers based on digital hysteresis to enhance both the sensitivity and the specificity simultaneously. The pulsating voltage transcranial electrical stimulator (PVTES) automatically configures the number of pulses to control the amount of charge delivered based on skin-electrode impedance variation in efforts to suppress the seizure activity, while burning only 2.45 mu W. The 25 mm(2) SoC implemented in 0.18 mu m CMOS consumes 2.73 mu J/classification for 16 channels with an average sensitivity, specificity, and latency of 95.7%, 98%, and 1 s, respectively.-
dc.language영어-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleA 16-Channel Patient-Specific Seizure Onset and Termination Detection SoC With Impedance-Adaptive Transcranial Electrical Stimulator-
dc.typeArticle-
dc.identifier.doi10.1109/JSSC.2015.2482498-
dc.citation.journaltitleIEEE JOURNAL OF SOLID-STATE CIRCUITS-
dc.identifier.wosid000364458200023-
dc.identifier.scopusid2-s2.0-84947046618-
dc.citation.endpage2740-
dc.citation.number11-
dc.citation.startpage2728-
dc.citation.volume50-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorYoo, Jerald-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.subject.keywordPlusEEG ACQUISITION SOC-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusSENSOR-
dc.subject.keywordPlusMACHINE-
dc.subject.keywordPlusNEUROSTIMULATION-
dc.subject.keywordPlusSUPPRESSION-
dc.subject.keywordPlusPROCESSOR-
dc.subject.keywordPlusELECTRODE-
dc.subject.keywordPlusEPILEPSY-
dc.subject.keywordPlusCMOS-
dc.subject.keywordAuthorAnalog sleep mode-
dc.subject.keywordAuthorcharge recycling-
dc.subject.keywordAuthorcontinuous health monitoring-
dc.subject.keywordAuthordigital hysteresis-
dc.subject.keywordAuthorelectroencephalogram (EEG)-
dc.subject.keywordAuthorepilepsy-
dc.subject.keywordAuthormachine learning-
dc.subject.keywordAuthornoninvasive-
dc.subject.keywordAuthorseizure detection-
dc.subject.keywordAuthorsupport vector machine (SVM)-
dc.subject.keywordAuthorsystem-on-chip (SoC)-
dc.subject.keywordAuthortranscranial electrical stimulation-
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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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