R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope

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 rapi...

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Main Authors: Jeong-Seon Park, Sang-Woong Lee, Unsang Park
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Journal of Healthcare Engineering
Online Access:http://dx.doi.org/10.1155/2017/4901017
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spelling doaj-fcf5efa34a5a4f72b978c17e666730172020-11-24T22:57:47ZengHindawi LimitedJournal of Healthcare Engineering2040-22952040-23092017-01-01201710.1155/2017/49010174901017R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy EnvelopeJeong-Seon Park0Sang-Woong Lee1Unsang Park2Department of Multimedia, Chonnam National University, 50 Daehak-ro, Yeosu, Jeollanamdo 59626, Republic of KoreaDepartment of Software, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam, Gyeonggido 13120, Republic of KoreaDepartment of Computer Science & Engineering, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul 04107, Republic of KoreaRapid 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.http://dx.doi.org/10.1155/2017/4901017
collection DOAJ
language English
format Article
sources DOAJ
author Jeong-Seon Park
Sang-Woong Lee
Unsang Park
spellingShingle Jeong-Seon Park
Sang-Woong Lee
Unsang Park
R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope
Journal of Healthcare Engineering
author_facet Jeong-Seon Park
Sang-Woong Lee
Unsang Park
author_sort Jeong-Seon Park
title R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope
title_short R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope
title_full R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope
title_fullStr R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope
title_full_unstemmed R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope
title_sort r peak detection method using wavelet transform and modified shannon energy envelope
publisher Hindawi Limited
series Journal of Healthcare Engineering
issn 2040-2295
2040-2309
publishDate 2017-01-01
description 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.
url http://dx.doi.org/10.1155/2017/4901017
work_keys_str_mv AT jeongseonpark rpeakdetectionmethodusingwavelettransformandmodifiedshannonenergyenvelope
AT sangwoonglee rpeakdetectionmethodusingwavelettransformandmodifiedshannonenergyenvelope
AT unsangpark rpeakdetectionmethodusingwavelettransformandmodifiedshannonenergyenvelope
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