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Detection of Qrs Complex in Electrocardiogram Signal Based on a Combination of Hilbert Transform, Wavelet Transform and Adaptive Thresholding Publisher



Farahabadi A1 ; Farahabadi E1 ; Rabbani H2 ; Mahjoub MP3
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Authors Affiliations
  1. 1. Biomedical Engineering Dept., School of Medicine, Isfahan Univ. of Medical Sciences, Isfahan, Iran
  2. 2. Biomedical Engineering Dept., Medical Image and Signal Processing Research Center, Isfahan Univ. of Medical Sciences, Isfahan, Iran
  3. 3. School of Medicine, Shahid Beheshti Univ. of Medical Sciences, Tehran, Iran

Source: Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012 Published:2012


Abstract

Electrocardiogram (ECG) signal is one of the most important and most used biologic signals which have a significant role in diagnosis of heart diseases. Extraction of QRS complex and obtaining its characteristics is one of the most important parts in ECG signal processing. R wave is one of the main sections of QRS complex which has the essential role in determining and diagnosis of heart rhythm irregularities and also in determining heart rate variability (HRV). In this paper, we suggest a new algorithm by using a combination of Hilbert transform, wavelet transform and adaptive thresholding. We apply our algorithm on various ECG signals to evaluate its performance and see the proposed method outperforms other methods. All signals proposed in this paper except signals used in modeling part (that use simulated ECG signal in MATLAB software) are form MIT-BIH database. © 2012 IEEE.
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