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Respiratory rate extraction from single-lead ECG using homomorphic filtering.

Hemant Sharma1, K K Sharma1, Om Lata Bhagat2

  • 1Department of Electronics & Communication, Malaviya National Institute. Of Technology, Jaipur 302017, India.

Computers in Biology and Medicine
|February 21, 2015
PubMed
Summary

This study introduces a new method for extracting respiratory signals from ECGs using generalized homomorphic filtering. The discrete Fourier transform (DFT) based approach shows superior performance compared to DCT and R peak methods for ECG-derived respiration (EDR).

Keywords:
DFTECGECG derived respiration (EDR)Homomorphic filteringRespiration

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Area of Science:

  • Biomedical Engineering
  • Signal Processing

Background:

  • Electrocardiogram (ECG) signals contain valuable physiological information beyond cardiac activity.
  • Extracting respiratory information from single-lead ECG is crucial for non-invasive patient monitoring.
  • Existing methods for ECG-derived respiration (EDR) have limitations in accuracy and complexity.

Purpose of the Study:

  • To develop and evaluate a novel technique for respiratory signal extraction from single-lead ECG using generalized homomorphic filtering.
  • To compare the performance of Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT) within the generalized homomorphic filtering framework.
  • To assess the efficacy of the proposed EDR technique against established methods like Principal Component Analysis (PCA) and the R peak amplitude algorithm.

Main Methods:

  • A new EDR technique based on generalized homomorphic filtering is proposed.
  • Band-pass filtering is applied to the cepstrum of the ECG signal to isolate the respiratory component.
  • The Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT) are employed as the underlying transforms for homomorphic filtering.

Main Results:

  • The EDR signal derived using generalized homomorphic filtering with DFT demonstrated superior performance compared to DCT.
  • Performance was evaluated using correlation, magnitude squared coherence coefficients, and breath rate accuracy against a reference respiratory signal.
  • The proposed DFT-based EDR technique (RDFT) significantly outperformed the R peak amplitude algorithm.

Conclusions:

  • Generalized homomorphic filtering using DFT offers an effective approach for EDR extraction from single-lead ECG.
  • The RDFT method shows significant improvement over the R peak amplitude algorithm.
  • While promising, the RDFT technique did not show significant improvements over the PCA-based EDR method, suggesting areas for future research.