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

Inactive Publication Date: 2021-01-08
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0008] In order to solve the problem of difficult feature extraction of autism EEG signals in the prior art, the present invention realizes the purpose of classification of autism EEG signals

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  • Autism electroencephalogram signal classification device based on resting-state brain network
  • Autism electroencephalogram signal classification device based on resting-state brain network
  • Autism electroencephalogram signal classification device based on resting-state brain network

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Embodiment Construction

[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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Abstract

The invention discloses an autism electroencephalogram signal classification device based on a resting-state brain network, belongs to the technical field of biomedical information, and particularly relates to a pattern classification method in the field of brain-computer interfaces. According to the device, autism is recognized and diagnosed from the three aspects of information entropy, power spectrum and brain function network, the most common electroencephalogram signal analysis method at the current research stage is included, an SPN filter is innovatively used for diagnosing the autism patient, and the accuracy rate is close to 100%. Particularly, by researching resting-state brain networks of autism children and normal children, the network topology difference of the autism childrenand the normal children is explored, and comparison with other various methods is performed, so that the pathology of autism is explored to a certain extent, and a reliable basis is provided for clinical diagnosis of autism.

Description

technical field [0001] The invention belongs to the technical field of biomedical information, in particular to a pattern classification method in the field of brain-computer interface. Background technique [0002] Autism, also known as autism, is a type of Autism Spectrum Disorder (ASD). Most people with autism start to have similar symptoms in infancy, and the disorder is more common in boys. There are many ways to assess and diagnose autism in clinical and research. These diagnostic methods mainly include behavioral scales, functional MRI, magnetoencephalography, and EEG. In recent years, fMRI research results on autism have increased, but its temporal resolution is low, and its specificity and sensitivity are not high when diagnosing a single subject. Magnetoencephalography (MEG) is a non-invasive neuroimaging method, but its technical history is relatively short, and the price is high, and further innovation is still needed. [0003] Brain Computer Interface (BCI) ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/16A61B5/369A61B5/372A61B5/374A61B5/00
CPCA61B5/165A61B5/7264
Inventor 李发礼张树李存波尧德中冯睿许文明徐鹏
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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