Accurate assessment of low-function autistic children based on EEG feature fusion

Jiannan Kang; Yajuan Jin; Guanhao Liang; Xiaoli Li

doi:10.1016/j.jocn.2021.06.022

Accurate assessment of low-function autistic children based on EEG feature fusion

J Clin Neurosci. 2021 Aug:90:351-358. doi: 10.1016/j.jocn.2021.06.022. Epub 2021 Jun 23.

Authors

Jiannan Kang¹, Yajuan Jin², Guanhao Liang³, Xiaoli Li⁴

Affiliations

¹ Institute of Electronic Information Engineering, Hebei University, Baoding, China; The State Key Laboratory for Management and Control of Complex Systems, Beijing, China.
² Institute of Electronic Information Engineering, Hebei University, Baoding, China.
³ State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
⁴ State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China. Electronic address: xiaoli@bnu.edu.cn.

PMID: 34275574
DOI: 10.1016/j.jocn.2021.06.022

Abstract

Autism spectrum disorder (ASD) is a very serious neurodevelopmental disorder and diagnosis mainly depends on the clinical scale, which has a certain degree of subjectivity. It is necessary to make accurate evaluation by objective indicators. In this study, we enrolled 96 children aged from 3 to 6 years: 48 low-function autistic children (38 males and 10 females; mean±SD age: 4.9±1.1 years) and 48 typically developing (TD) children (38 males and 10 females; mean±SD age: 4.9 ± 1.2 years) to participate in our experiment. We investigated to fuse multi-features (entropy, relative power, coherence and bicoherence) to distinguish low-function autistic children and TD children accurately. Minimum redundancy maximum correlation algorithm was used to choose the features and support vector machine was used for classification. Ten-fold cross validation was used to test the accuracy of the model. Better classification result was obtained. We tried to provide a reliable basis for clinical evaluation and diagnosis for ASD.

Keywords: ASD; Assessment; Children; EEG; Multi-feature.

MeSH terms

Algorithms
Autism Spectrum Disorder / classification
Autism Spectrum Disorder / diagnostic imaging
Autistic Disorder / classification*
Autistic Disorder / diagnosis*
Child
Child, Preschool
Electroencephalography / methods*
Entropy
Female
Humans
Male
Reference Values
Support Vector Machine