The Application of Frequency Slice Wavelet Transform in ECG Signal Feature Extraction (Journal of Fiber Bioengineering and Informatics, 2015)
According to the difference of time-frequency characteristics of ECG (electrocardiogram) signal andjamming signal, FSWT (Frequency Slice Wavelet Transform) is used to deal with the ECG signaldenoising and feature extraction. FSWT algorithm has a good time-frequency aggregation and can freelychoose the frequency range for signal reconstruction to extract characteristic information flexibly andaccurately. Firstly, ECG signal is decomposed to get the whole time-frequency distribution characteristicby using FSWT and carries on the detailed analysis. Frequency section interval is determined accordingto frequency distribution characteristics of the jamming signal, disturbance signal is refactored andisolated through the time-frequency filter and the inverse transformation of FSWT. So it can realize theECG signal denoising and feature extraction. The proposed algorithm is compared with wavelet thresholddenoising method, Empirical Mode Decomposition (EMD) and average empirical mode decomposition(AIMF). The simulation results show that, the denoising effect of FSWT is superior to other methodsfor ECG signal, and gives the time-frequency distribution characteristics of ECG signal.