Evaluation of the gross motor abilities of autistic children with a computerised evaluation method

Xiaodi Liu, Jingying Chen, Guangshuai Wang, Kun Zhang, Jianchi Sun, Pianpian Ma and Rujing Zhang

Behaviour and Information Technology, 2024, vol. 43, issue 13, 3261-3270

Abstract: To effectively evaluate the gross motor ability of autistic children, we proposed a method of computerised evaluation of gross motor skills (CEGM). The CEGM integrates Dynamic Time Warping (DTW) method and OpenPose technology to automatically detect key joints and return a score. Ten items were selected for evaluation based on the gross motor subtest of the Psychoeducational Profile – Third Edition (PEP-3) scale, including upper limb movement, lower limb movement, and body coordination performance. 30 autistic participants (males: 23, female: 7) with an average age of 5.00 years were recruited in this study. Then we compared the results of evaluation using CEGM and the original PEP-3 gross motor subtest in autistic children. The results showed that in the evaluations using CEGM and PEP-3, Cronbach’s α coefficients and Spearman-rank correlation coefficients were all greater than 0.80, intraclass correlation coefficient (ICC) were all greater than 0.90, indicating good agreement in evaluating the gross motor ability of autistic children. Moreover, compared to the PEP-3, the evaluation using CEGM provided precise quantitative indicators (trajectory, velocity, and angle of joint). Therefore, our findings demonstrate that CEGM can be used in the initial evaluation of the gross motor ability of autistic children.

Date: 2024
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DOI: 10.1080/0144929X.2023.2275163

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