早期帕金森疾病脑电信号的复杂度分析

Complexity analysis of the EEG activity in patients with early-stage Parkinson's disease

为了研究早期帕金森疾病脑电活动异常,记录了27名帕金森早期病人和27名年龄匹配的健康对照组在静息状态下的20导EEG信号。采用排序熵和规则性指数,刻画了2组脑电图数据的复杂性特征。与对照组相比,早期帕金森病人的排序熵降低,规则性指数升高,表明静息状态下帕金森早期组的EEG复杂度低于健康对照组。研究发现,排序熵和规则性指数能有效地刻画帕金森疾病脑电信号的复杂度异常,可为该疾病的早期检测提供一项有效的生物标记。

To investigate the abnormality of the brain activity in patients with early-stage Parkinson’s disease (PD),20 chan-nel electroencephalograph(EEG)signals were recorded from 27 patients in early stages of non-dementia PD and 27 age-matched healthy controls during rest.The permutation entropy (PE)and order index (OI)were adopted to characterize the complexity of the recorded EEG data for the two groups.It is found that the EEG of PD patients shows a lower PE value and a higher OI value than that of the controls,which indicates that the resting EEG complexity in PD is less than that in healthy controls.The result demonstrates that the PE and OI measures are promising methods to reveal the abnormal changes associated with PD, which may provide a biomarker for detecting the early-stage Parkinson’s disease.