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A 1.52 uJ/classification Patient-Specific Seizure Classification Processor using Linear SVM
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Bin Altaf, Muhammad Awais | - |
dc.contributor.author | Yoo, Jerald | - |
dc.date.accessioned | 2024-05-03T04:34:42Z | - |
dc.date.available | 2024-05-03T04:34:42Z | - |
dc.date.created | 2024-05-02 | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | IEEE International Symposium on Circuits and Systems proceedings, pp.849-852 | - |
dc.identifier.issn | 0271-4302 | - |
dc.identifier.uri | https://hdl.handle.net/10371/200842 | - |
dc.description.abstract | This paper presents an 8-channel electroencephalograph (EEG) classification processor for seizure detection and recording. To integrate 8 channels, an area- and energy-efficient filter architecture using Distributed Quad-LUT (DQ-LUT) is proposed, which reduces area by 64.2% with minimal overhead in power. delay product. The on-chip patient specific classification with a Linear Support-Vector Machine (SVM) results in 82.7% seizure detection accuracy with a 2 second latency using the CHB-MIT EEG database [1]. The overall energy efficiency is measured | - |
dc.language | 영어 | - |
dc.publisher | IEEE | - |
dc.title | A 1.52 uJ/classification Patient-Specific Seizure Classification Processor using Linear SVM | - |
dc.type | Article | - |
dc.citation.journaltitle | IEEE International Symposium on Circuits and Systems proceedings | - |
dc.identifier.wosid | 000332006801026 | - |
dc.identifier.scopusid | 2-s2.0-84883384202 | - |
dc.citation.endpage | 852 | - |
dc.citation.startpage | 849 | - |
dc.description.isOpenAccess | N | - |
dc.contributor.affiliatedAuthor | Yoo, Jerald | - |
dc.type.docType | Proceedings Paper | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordPlus | EEG ACQUISITION SOC | - |
dc.subject.keywordPlus | EPILEPTIC SEIZURES | - |
dc.subject.keywordPlus | SYSTEM | - |
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- College of Engineering
- Department of Electrical and Computer Engineering
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