Classification of Normal and Pathological Gait in Young Children Based on Foot Pressure Data

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• 作者：Guodong Guo ; Keegan Guffey ; Wenbin Chen ; Paola Pergami
• 关键词：Normal/pathological gait recognition ; GAITRite walkway system ; Medical instrument ; Health application
• 刊名：Neuroinformatics
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：15
• 期：1
• 页码：13-24
• 全文大小：
• 刊物主题：Neurosciences; Bioinformatics; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Neurology;
• 出版者：Springer US
• ISSN：1559-0089
• 卷排序：15

文摘

Human gait recognition, an active research topic in computer vision, is generally based on data obtained from images/videos. We applied computer vision technology to classify pathology-related changes in gait in young children using a foot-pressure database collected using the GAITRite walkway system. As foot positioning changes with children’s development, we also investigated the possibility of age estimation based on this data. Our results demonstrate that the data collected by the GAITRite system can be used for normal/pathological gait classification. Combining age information and normal/pathological gait classification increases the accuracy of the classifier. This novel approach could support the development of an accurate, real-time, and economic measure of gait abnormalities in children, able to provide important feedback to clinicians regarding the effect of rehabilitation interventions, and to support targeted treatment modifications.