A New Mixed Clustering-Based Method to Analyze the Gait of Children with Cerebral Palsy
作者机构：Department of Rehabilitation MedicineChildren’s Hospital of Nanjing Medical UniversityNanjing210008China Liaoning Children’s HospitalShenyang110085China Shenyang Jing’an Mental Health HospitalShenyang110163China Department of Physics and AstronomyUniversity College LondonLondon0044UK
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2021年第66卷第2期
页 面：1551-1562页
核心收录：
基 金：J.Li gratefully acknowledge the financial support by the NSFC(61772280) http://www.nsfc.gov.cn
主 题：Cerebral palys gait analysis children mixed clustering
摘 要：Cerebral palsy is a group of persistent central movement and posturaldevelopmental disorders, and restricted activity syndromes. This syndrome iscaused by non-progressive brain damage to the developing fetus or infants. Cerebralpalsy assessment can determine whether the brain is behind or abnormal. If itexists, early intervention and rehabilitation can be carried out as soon as possibleto restore brain function to the greatest extent. The direct external manifestation ofcerebral palsy is abnormal gait. Accurately determining the muscle strengthrelatedreasons that cause this abnormal gait is the primary problem for *** this paper, clustering methods were used to compare and analyze the differencesbetween the abnormal and normal gait parameters of children with andwithout cerebral palsy. Since the collected data contains overlapping data thatmay be mutated, while the centroids are also different, the expected result is *** solve this problem, a mixed clustering method is proposed that combinesthe advantages of K-means and hierarchical clustering, meaning that eachset of data shows a similar trend to specific parameters. Experiment results showthat this method can detect cerebral palsy through the difference between theabnormal gait of children with cerebral palsy and that of normal children.
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