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Cited 30 time in webofscience Cited 68 time in scopus
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R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope

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dc.contributor.authorPark, Jeong-Seon-
dc.contributor.authorLee, Sang-Woong-
dc.contributor.authorPark, Unsang-
dc.date.available2020-02-27T23:42:24Z-
dc.date.created2020-02-07-
dc.date.issued2017-07-
dc.identifier.issn2040-2295-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/7531-
dc.description.abstractRapid automatic detection of the fiducial points-namely, the P wave, QRS complex, and T wave-is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs.-
dc.language영어-
dc.language.isoen-
dc.publisherHINDAWI LTD-
dc.relation.isPartOfJOURNAL OF HEALTHCARE ENGINEERING-
dc.titleR Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000405719900001-
dc.identifier.doi10.1155/2017/4901017-
dc.identifier.bibliographicCitationJOURNAL OF HEALTHCARE ENGINEERING, v.2017-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-85024479769-
dc.citation.titleJOURNAL OF HEALTHCARE ENGINEERING-
dc.citation.volume2017-
dc.contributor.affiliatedAuthorLee, Sang-Woong-
dc.type.docTypeArticle-
dc.subject.keywordPlusECG SIGNAL-
dc.subject.keywordPlusFEATURE-EXTRACTION-
dc.subject.keywordPlusNOISE REMOVAL-
dc.subject.keywordPlusQRS-
dc.subject.keywordPlusELECTROCARDIOGRAM-
dc.relation.journalResearchAreaHealth Care Sciences & Services-
dc.relation.journalWebOfScienceCategoryHealth Care Sciences & Services-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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