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An Improved R-Peaks Marking Method Using Fourier Decomposition and Teager Energy Operator
Author(s) -
Ponnam Harikrishna,
Jakeer Hussain Shaik
Publication year - 2020
Publication title -
traitement du signal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.279
H-Index - 11
eISSN - 1958-5608
pISSN - 0765-0019
DOI - 10.18280/ts.370319
Subject(s) - energy operator , fourier transform , energy (signal processing) , decomposition , operator (biology) , computer science , speech recognition , mathematics , artificial intelligence , pattern recognition (psychology) , statistics , chemistry , mathematical analysis , biochemistry , organic chemistry , repressor , transcription factor , gene
Received: 11 February 2020 Accepted: 26 May 2020 The exact discovery of R-peak becomes very much crucial while extracting prominent features from Electrocardiogram (ECG) signal. However, identification of R-peaks precisely becomes more challenging due to contamination of noise and fragmented QRS complexes. This paper presents an improved method of marking R-peaks. Initially, an efficient Fourier Decomposition Methodology (FDM) is used for removing noise. The accuracy of finding R-peaks can be improved by enhancing the QRS complexes using Teager Energy Operator. Hilbert Transform and Zero Cross Detector (ZCD) are used for marking the R-peaks. The MIT-BIH arrhythmia database is used for validating the proposed scheme and attained 99.97% accuracy, 99.98% of sensitivity and 99.98% of positive predictivity. The findings proved that proposed method is superior as compared to the proven techniques in the literature.

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