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

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...

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Published inInternational journal of system assurance engineering and management Vol. 13; no. 5; pp. 2391 - 2403
Main Authors Gupta, Varun, Saxena, Nitin Kumar, Kanungo, Abhas, Kumar, Parvin, Diwania, Sourav
Format Journal Article
LanguageEnglish
Published New Delhi Springer India 01.10.2022
Springer Nature B.V
Subjects
Algorithms
Arrhythmia
Electrocardiography
Engineering
Engineering Economics
Feature extraction
Fourier transforms
Inspection
Logistics
Marketing
Organization
Original Article
Principal components analysis
Quality Control
Reliability
Safety and Risk
Signal processing
Visual signals
Electrocardiogram (ECG)
MIT-BIH arrhythmia database
Fractional Fourier transform (FrFT)
Principal component analysis (PCA)
Online AccessGet full text
ISSN0975-6809
0976-4348
DOI10.1007/s13198-022-01650-0

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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.
AbstractList 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.
Author Gupta, Varun
Diwania, Sourav
Kumar, Parvin
Saxena, Nitin Kumar
Kanungo, Abhas
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The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2022.
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– notice: The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2022.
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Keywords Electrocardiogram (ECG)
MIT-BIH arrhythmia database
Fractional Fourier transform (FrFT)
Principal component analysis (PCA)
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Snippet Visual inspection of R-peaks in Electrocardiogram (ECG) signal is avoided because of limited resolution and in the variation of parameters of the underlying...
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springer
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StartPage 2391
SubjectTerms Algorithms
Arrhythmia
Electrocardiography
Engineering
Engineering Economics
Feature extraction
Fourier transforms
Inspection
Logistics
Marketing
Organization
Original Article
Principal components analysis
Quality Control
Reliability
Safety and Risk
Signal processing
Visual signals
Title PCA as an effective tool for the detection of R-peaks in an ECG signal processing
URI https://link.springer.com/article/10.1007/s13198-022-01650-0
https://www.proquest.com/docview/2727217994
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