Validation of μ-volt T-wave alternans analysis using multiscale analysis-by-synthesis and higher-order SVD. (February 2018)

• Record Type: Journal Article
• Authors: Padhy, Sibasankar; Dandapat, S.
• Is Part Of: Biomedical signal processing and control. Volume 40(2018)
• Page Start: 171
• Page End: 179
• Publication Date: 2018-02
• Subjects: Higher-order singular value decomposition -- Multilead ECG -- Multiscale analysis-by-synthesis -- T-wave alternans -- Tensor decomposition; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2017.09.013
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: A multiscale analysis-by-synthesis and higher-order SVD based TWA detection algorithm is proposed. MAS and HOSVD removes TWA's out- and in-band unwanted components which helps improve TWA analysis performance. High sensitivity for TWA detection (95.2%) has been observed for 10 μV alternans level. Estimated TWA levels are close to the added or observed alternans levels (for semi-synthetic or real signals). The MAS–HOSVD method estimates lead-wise TWA amplitude levels simultaneously. Abstract: Detection of microvolt T-wave alternans (TWA) and finding its clinical significance remains a challenging task. In this work, we propose a new TWA detection method based on multiscale analysis-by-synthesis followed by higher-order singular value decomposition (MAS–HOSVD). The multilead ECG (MECG) data, after R-peak detection, were represented as a third-order tensor. Then HOSVD was applied on the subband reconstructed T-wave tensor to determine a tensor containing T-wave information (TensorTinfo). The p -value, TWA ratio, and the probability of detection ( P D ) were computed, based on the information present in TensorTinfo, to validate the presence of TWA or not. The proposed method was evaluated with semi-synthetic and real signals by adding several types of noise at different SNR levels and was compared to a multilead and two single-lead schemes. Simulation results showed that the proposed method detected TWA accurately with the sensitivity of 95.2% for the alternans level of 10 μV. Also, the method detected TWA with an SNR at least lower by 10 dB than other methods. The MAS–HOSVD method was tested to be accurate in TWA analysis of MECG data. This method can be considered as an automatic tool for prior prognosticator of sudden cardiac death, consequently, can help reduce the mortality rate.