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ECG Signal Analysis and Arrhythmia Detection using Wavelet Transform

  • Inderbir Kaur
  • Rajni Rajni
  • Anupma Marwaha
Original Contribution

Abstract

Electrocardiogram (ECG) is used to record the electrical activity of the heart. The ECG signal being non-stationary in nature, makes the analysis and interpretation of the signal very difficult. Hence accurate analysis of ECG signal with a powerful tool like discrete wavelet transform (DWT) becomes imperative. In this paper, ECG signal is denoised to remove the artifacts and analyzed using Wavelet Transform to detect the QRS complex and arrhythmia. This work is implemented in MATLAB software for MIT/BIH Arrhythmia database and yields the sensitivity of 99.85 %, positive predictivity of 99.92 % and detection error rate of 0.221 % with wavelet transform. It is also inferred that DWT outperforms principle component analysis technique in detection of ECG signal.

Keywords

Electrocardiogram Discrete wavelet transform (DWT) Denoising QRS detection Arrhythmia 

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Copyright information

© The Institution of Engineers (India) 2016

Authors and Affiliations

  1. 1.Shaheed Bhagat Singh State Technical CampusFerozepurIndia
  2. 2.Sant Longowal Institute of Engineering and TechnologyLongowal, SangrurIndia

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