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dc.contributor.author Seol, Tae Ryoung ko
dc.contributor.author Lee, Se Hwan ko
dc.contributor.author Lee, Jung Hyup ko
dc.date.accessioned 2021-01-22T07:20:45Z -
dc.date.available 2021-01-22T07:20:45Z -
dc.date.created 2021-01-13 -
dc.date.issued 2021-01 -
dc.identifier.citation IDEC Journal of Integrated Circuits and Systems, v.7, no.1, pp.1 - 5 -
dc.identifier.issn 2384-2113 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/12733 -
dc.description.abstract This study proposes a wearable system that can measure electrocardiogram (ECG) signals reliably in an environment with high motion artifacts. This system employs a motion artifact extraction method based on a triple-axis accelerometer attached to each electrode independently to remove motion artifacts from ECG signals with high performance. Recursive Least Square (RLS) and Least Mean Square (LMS) algorithms remove extracted noise from the source signals, thereby obtaining a mean square error (MSE) of 0.0166 when using RLS and 0.0160 when using LMS. This means that the performance improved respectively by approximately 5.1% and 8.6% compared to that of the recently developed ECG monitoring system. -
dc.language English -
dc.publisher 반도체설계교육센터 -
dc.title A Wearable Electrocardiogram Monitoring System Robust to Motion Artifacts -
dc.type Article -
dc.type.local Article(Domestic) -
dc.type.rims ART -
dc.description.journalClass 2 -
dc.identifier.kciid ART002665126 -
dc.contributor.localauthor Lee, Jung Hyup -
dc.identifier.citationVolume 7 -
dc.identifier.citationNumber 1 -
dc.identifier.citationStartPage 1 -
dc.identifier.citationEndPage 5 -
dc.identifier.citationTitle IDEC Journal of Integrated Circuits and Systems -
dc.type.journalArticle Article -
dc.description.isOpenAccess Y -
dc.subject.keywordAuthor Adaptive filtering Electrocardiogram (ECG) -
dc.subject.keywordAuthor Mean Squared Error (MSE) -
dc.subject.keywordAuthor Motion artifact -


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