Evaluation Method of Motor Coordination Ability in Children Based on Machine Vision  

作　　者：Yi Lei Dawei Shu Miao Yu Donglin Shi Jianqiang Li Yanjie Chen 

机构地区：[1]Faculty of Information Technology,Beijing University of Technology,Beijing 100124,China [2]Department of Automation,Tsinghua University,Beijing 100084,China [3]Pharmacovigilance Research Center for information technology and Data Science,Cross-strait Tsinghua Research Institute,Xiamen 361000,China [4]Institute of Systems Engineering,Dalian University of Technology,Dalian 116024,China [5]Physical Education Department,Hebei Sports University,Shijiazhuang 050049,China [6]Department of Children’s Health Care Center,Beijing Children’s Hospital,Capital Medical University,National Center for Children’s Health,Beijing 100045,China

出　　处：《Tsinghua Science and Technology》2025年第2期633-649,共17页清华大学学报自然科学版(英文版)

基　　金：supported by the National Key Research and Development Program of China(No.2020YFB2104402).

摘　　要：Motor coordination is crucial for preschoolers’development and is a key factor in assessing childhood development.Current diagnostic methods often rely on subjective manual assessments.This paper presents a machine vision-based approach aimed at improving the objectivity and adaptability of assessments.The method proposed involves the extraction of key points from the human skeleton through the utilization of a lightweight pose estimation network,thereby transforming video assessments into evaluations of keypoint sequences.The study uses different methods to handle static and dynamic actions,including regularization and Dynamic Time Warping(DTW)for spatial alignment and temporal discrepancies.A penalty-adjusted single-frame pose similarity method is used to evaluate actions.The lightweight pose estimation model reduces parameters by 85%,uses only 6.6%of the original computational load,and has an average detection missing rate of less than 1%.The average error for static actions is 0.071 with a correlation coefficient of 0.766,and for dynamic actions it is 0.145 with a correlation coefficient of 0.653.These results confirm the proposed method’s effectiveness,which includes customized visual components like motion waveform graphs to improve accuracy in pediatric healthcare diagnoses.

关 键 词：developmental coordination disorder action quality assessment pose estimation dynamic time warping decision support system 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]