R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope
DC Field | Value | Language |
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dc.contributor.author | Park, Jeong-Seon | - |
dc.contributor.author | Lee, Sang-Woong | - |
dc.contributor.author | Park, Unsang | - |
dc.date.available | 2020-02-27T23:42:24Z | - |
dc.date.created | 2020-02-07 | - |
dc.date.issued | 2017-07 | - |
dc.identifier.issn | 2040-2295 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/7531 | - |
dc.description.abstract | Rapid 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.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | HINDAWI LTD | - |
dc.relation.isPartOf | JOURNAL OF HEALTHCARE ENGINEERING | - |
dc.title | R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000405719900001 | - |
dc.identifier.doi | 10.1155/2017/4901017 | - |
dc.identifier.bibliographicCitation | JOURNAL OF HEALTHCARE ENGINEERING, v.2017 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-85024479769 | - |
dc.citation.title | JOURNAL OF HEALTHCARE ENGINEERING | - |
dc.citation.volume | 2017 | - |
dc.contributor.affiliatedAuthor | Lee, Sang-Woong | - |
dc.type.docType | Article | - |
dc.subject.keywordPlus | ECG SIGNAL | - |
dc.subject.keywordPlus | FEATURE-EXTRACTION | - |
dc.subject.keywordPlus | NOISE REMOVAL | - |
dc.subject.keywordPlus | QRS | - |
dc.subject.keywordPlus | ELECTROCARDIOGRAM | - |
dc.relation.journalResearchArea | Health Care Sciences & Services | - |
dc.relation.journalWebOfScienceCategory | Health Care Sciences & Services | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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