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Adaptive time-frequency matrix features for T wave alternans analysis
Behnaz Ghoraani1, Sridhar Krishnan, Raja J Selvaraj
1Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada, M5B 2K3.
Summary
This study introduces a new Non-negative Matrix Factorization (NMF)-Adaptive spectral method for robust T wave alternans (TWA) detection in ambulatory ECGs. The NMF method significantly improves TWA detection accuracy, aiding in risk stratification for sudden cardiac death.
Area of Science:
- Cardiology
- Biomedical Engineering
- Signal Processing
Background:
- T wave alternans (TWA) is linked to ventricular arrhythmias and sudden cardiac death.
- Accurate TWA detection is challenging due to low signal amplitude and biological noise in ambulatory ECGs.
Purpose of the Study:
- To develop a robust method for TWA detection in ambulatory electrocardiograms (ECGs).
- To improve risk stratification for patients with heart disease prone to sudden cardiac death.
Main Methods:
- Proposed a Non-negative Matrix Factorization (NMF)-Adaptive spectral method.
- Applied non-linear time-frequency (TF) analysis and NMF to aligned ST-T waveforms.
- Separated TWA signals from other ECG components.
Main Results:
- Achieved 92% TWA detection accuracy.
- Conventional spectral methods achieved only 47% accuracy.
- Validated performance in a clinical study using ambulatory ECGs.
Conclusions:
- The NMF-Adaptive spectral method enhances TWA detection robustness and accuracy.
- This method offers improved risk stratification for patients at risk of sudden cardiac death.
- The technique effectively isolates TWA signals from noise in ambulatory ECGs.
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