Identify Sudden Cardiac Death Based on Cyclostationary Characteristics of ECG Signal

Aiming at sudden cardiac death diseases identification accuracy is not high, a new method is proposed to extract the cyclostationary characteristics of ECG signal. We denoise ECG signal through the wavelet transform. Based on the cyclostationary features of ECG signal, we adopt the method of cyclic spectrum estimation in cyclic frequencey domain to extract cyclostationary characteristics. Support vector machine is used to identify the sudden cardiac death. The results show that cyclic frequence average can especially reflect the cyclostationary characteristics of ECG signal and accurately identify the sudden cardiac death. Sudden death of ECG signal recognition accuracy up to reach 97.50%.