PCA as an effective tool for the detection of R-peaks in an ECG signal processing

Varun Gupta (), Nitin Kumar Saxena, Abhas Kanungo, Parvin Kumar and Sourav Diwania
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Varun Gupta: KIET Group of Institutions
Nitin Kumar Saxena: KIET Group of Institutions
Abhas Kanungo: KIET Group of Institutions
Parvin Kumar: KIET Group of Institutions
Sourav Diwania: KIET Group of Institutions

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 5, No 20, 2403 pages

Abstract: Abstract Visual inspection of R-peaks in Electrocardiogram (ECG) signal is avoided because of limited resolution and in the variation of parameters of the underlying subject (patient). Therefore, Principal Component Analysis has been used for R-peak detection without any pre-processing in noisy and different morphologies of the ECG signal with fractional Fourier transform which is using as a feature extraction technique. For validating this research work MIT-BIH Arrhythmia database is considered. The performance of developed algorithm is judged based on sensitivity, positive predictive value and accuracy. It has been revealed that the developed algorithm is capable to analyze ECG signals in both situations either normal or abnormal. It opens their huge applications in the time varying signals which can capture important clinical attributes in critical pathological situations.

Keywords: Electrocardiogram (ECG); Fractional Fourier transform (FrFT); Principal component analysis (PCA); MIT-BIH arrhythmia database (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-022-01650-0

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