期刊
IET SIGNAL PROCESSING
卷 7, 期 8, 页码 783-790出版社
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-spr.2012.0128
关键词
electrocardiography; entropy; medical signal detection; wavelet transforms; gain 5 dB; noise figure 30 dB; Symlet4 function; truncated Morlet function; Mexican Hat function; signal-to-noise ratio; simulated alternan waveform; continuous wavelet transform; relative wavelet energy coefficient; ventricular repolarisation complex; CTWE; TWA detection scheme; surface electrocardiography; malignant ventricular arrhythmias; microvolt T-wave alternan; prognostic utility; cardiac repolarisation alternan detection; continuous-time wavelet entropy
Prognostic utility of microvolt T-wave alternans (TWAs) has been established since its clinical acceptance as markers for malignant ventricular arrhythmias, leading to sudden cardiac death. Accurate detection of TWA from surface electrocardiography is a challenge because of invisible nature of the phenomenon. A novel TWA detection scheme based upon analysis of continuous-time wavelet entropy (CTWE) trend of consecutive ventricular repolarisation complexes is presented. The CTWE is computed using relative wavelet energy coefficients of continuous wavelet transform. Variety of simulated alternan waveforms, wavelet functions, frequency bands and noise levels are used to test the algorithm. The algorithm achieves a sensitivity of 100% at signal-to-noise ratio (SNR) >35 dB for all the selected wavelet functions and sensitivities of 99.5, 97 and 92% for Symlet4, Mexican Hat and truncated Morlet functions, respectively, at 30 dB SNR. A performance improvement of 5 dB is achieved by only computing the wavelet coefficients at the optimal frequency band. This study concludes that CTWE can successfully characterise the heterogeneity of cardiac repolarisation and detect TWA phenomenon.
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