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A novel approach is presented for analysis of surface electromyogram (EMG) morphology in Parkinson's disease (PD). The method is based on histogram and crossing rate (CR) analysis of EMG signal. In the method, histograms and CR values are used as high dimensional feature vectors. The dimensionality of them is then reduced using Karhunen-Loève transform (KLT). Finally, the discriminant analysis of feature vectors is performed in low dimensional eigenspace. Histograms and CR values were chosendoi:10.1088/0967-3334/28/12/005 pmid:18057515 fatcat:3zvrlry6azg7dlp23bfhapnvga