研究脑电波信号分析处理问题,由于不确定的信息较多,传统方法不能有效地从复杂的脑电波信号中获取应用于医学临床诊断的正确信息。分析异常脑电波信号特征,根据定性仿真理论对脑电波信号进行定性化处理,然后进行数据离散化,并根据Lemple-Ziv复杂度度量方法得到脑电波的定性复杂度。利用上述方法对实验数据进行了分析仿真,结果表明定性复杂度不仅可以用来区分脑癫痫波形和正常波形,而且还能很好地刻画癫痫发病过程中的不同阶段,为脑疾病患者的临床诊断提供了新途径。
This paper put forward a signal processing method for EEG signals in order to extract key information for clinical diagnosis.After analysed the characteristics of abnormal EEG,qualitative information was extracted based on qualitative simulation method.Furthermore,qualitative complexity of EEG signals were obtained through data discretization and by using Lemple-Ziv complexity measure method.Through a number of experiments,we have found that this qualitative complexity can reflect the character of the EEG,specialize the different phase of the disease,and can be used as a feature classifying the patient and normal person.