Autism electroencephalogram signal classification device based on resting-state brain network
A technology of EEG signal and brain network, applied in the fields of biomedical information and brain-computer interface, can solve problems such as difficulty in extracting features of autism EEG signal
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[0084] The present invention will be further described in conjunction with the accompanying drawings and specific embodiments.
[0085] S1. Collect experimental data. The present invention studies two batches of data collected, the first batch of data is a training set, and the second batch of data is a test set. The first batch of data included 16 autistic children (2-6 years old, average age 3.8 years, 13 females), and 11 normal children (3-5 years old, average age 7.42 years old, 8 females). The second batch of data included 11 children with autism (2-7 years old, mean age 4.82 years old, 9 females). The electrode placement standard is the international standard 10-20 system, the sampling rate is 500Hz, the band-pass filter range is 0.5-45Hz, and the resting state with eyes closed for 10 minutes is collected for each subject;
[0086] Calculate the sample entropy of each EEG channel in the training set (the first batch of data) delta, theta, alpha, and beta, and count the...
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