Automatic detection of epileptiform wave in EEG by multi-resolution analysis
基于多分辨分析的脑电癫痫波自动检测*

This paper proposed a new scheme for detecting epileptiform activity in 8-channel EEG based on the characteristic of a multi-resolution analysis. The EEG signal on each channel was decomposed to five levels using discrete wavelet transform. Formed wavelet coefficients and standard deviation of all 8-channel raw data to compute adaptive threshold, which applied on sub-bands1, 2 and 3. Then extracted the spike portion of EEG signal extracted from the raw data. The key points of this research work were identification of a suitable wavelet for decomposition of EEG signals, recognition of a proper resolution level, and computation of a dynamic threshold. The experiment results show that the proposed method offers a fast and effective measure for detecting epileptiform activity in human EEG.