Automatic detection of T wave alternans using tensor decompositions in multilead ECG signals

作者：Goovaerts Griet^*; Vandenberk Bert; Willems Rik; Van Huffel Sabine

来源：Physiological Measurement, 2017, 38(8): 1513-1528.

DOI：10.1088/1361-6579/aa7876

• biomedical signal processing
• tensors
• T wave alternans
• ECG signals

Objective: T wave alternans (TWA) is a promising non-invasive risk stratification tool for sudden cardiac death which can be detected from surface ECG. This paper proposes a novel method to automatically detect TWA based on tensor decomposition methods. Approach: Two different tensor decomposition approaches are examined and compared, namely canonical polyadic decomposition and the more generalized variation PARAFAC2 which allows the T waves to shift in time. Results and Significance: Results on different artificial and clinical signals show that the presented methods are a robust and reliable way for TWA detection, and show the potential benefit of tensors in ECG signal processing.

• 出版日期2017-8