文章基本信息

标题：Autism Spectrum Disorders Gait Identification Using Ground Reaction Forces
本地全文：下载
作者：Che Zawiyah Che Hasan ; Rozita Jailani ; Nooritawati Md Tahir 等
期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2017
卷号：15
期号：2
页码：903-911
DOI：10.12928/telkomnika.v15i1.6143
出版社：Universitas Ahmad Dahlan
其他摘要：Autism spectrum disorders (ASD) are a permanent neurodevelopmental disorder that can be identified during the first few years of life and are currently associated with the abnormal walking pattern. Earlier identification of this pervasive disorder could provide assistance in diagnosis and establish rapid quantitative clinical judgment. This paper presents an automated approach which can be applied to identify ASD gait patterns using three-dimensional (3D) ground reaction forces (GRF). The study involved classification of gait patterns of children with ASD and typical healthy children. The GRF data were obtained using two force plates during self-determined barefoot walking. Time-series parameterization techniques were applied to the GRF waveforms to extract the important gait features. The most dominant and correct features for characterizing ASD gait were selected using statistical between-group tests and stepwise discriminant analysis (SWDA). The selected features were grouped into two groups which served as two input datasets to the k-nearest neighbor (KNN) classifier. This study demonstrates that the 3D GRF gait features selected using SWDA are reliable to be used in the identification of ASD gait using KNN classifier with 83.33% performance accuracy.