Wave entropy of spontaneous dynamic activity based autism classification method

The invention discloses a wave entropy of spontaneous dynamic activity based autism classification method. The specific implementation steps of the method are as follows: (1) cutting near infrared spectroscopy fNIRS time sequences according to sequence lengths, setting different sliding windows and step lengths, performing spatial reconstruction on each subsequence according to the sliding windowsand the step lengths, and obtaining reconstruction components; (2) performing sample entropy calculating on the reconstruction components obtained by the step (1) so as to obtain a wave entropy sequence; (3) extracting four characteristic values (including the variance, mean, maximum and minimum of the wave entropy sequence) of the wave entropy sequence to generate a new sample as the input variable of a support vector machine (SVM); and (4) inputting the new sample obtained by the step (3) into the SVM to judge ASD. The method realizes high classification on ASD diagnosis; and the method indicates that the wave entr