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本文首次将小波变换模极大值对检测信号奇异点的理论应用于癫痫脑电信号，对棘波进行检测。采用二进样条小波对脑电信号按Ｍａｌａｔ算法进行变换，分析含有奇异点的信号，即棘波，与其小波变换模极大值对的关系，对棘波进行识别。从临床８例癫痫患者取出７５４个棘波进行验证，正确识别率可达９４．２％，并对两例正常脑电图无误检。
In this paper, for the first time, the theory of wavelet transform modulus maxima for singularity of detection signal is applied to epilepsy EEG signal to detect spikes. Using binary spline wavelet to transform the EEG signal according to Malat algorithm, the signal containing singular points, namely the spike wave, is analyzed and the relationship between the maximal value of wavelet transform module and the spike wave is identified. From the clinical 8 cases of epilepsy patients removed 754 spikes for verification, the correct recognition rate of up to 94.2%, and two cases of normal EEG without error.