John Edison Muñoz Cardona, J. F. Villada, S. Casanova, Maria Fernanda Montoya Vega, Ó. Henao
{"title":"人类运动的动态系统理论,通过使用Kinect的角度图探索协调模式","authors":"John Edison Muñoz Cardona, J. F. Villada, S. Casanova, Maria Fernanda Montoya Vega, Ó. Henao","doi":"10.1109/VS-Games.2018.8493416","DOIUrl":null,"url":null,"abstract":"Analyzing time series data using linear spatial/angular kinematics traditionally makes quantification of human movement using low-cost cameras such as the Kinect sensor. Through this conventional approach, interactions between body joints are difficult to analyze and coordination parameters remain hidden. Dynamic Systems Theory (DST) provides a non-linear framework to analyze human movement by representing intersegmental interactions in angle-angle diagrams. DST offers an accurate solution to study coordination in human movement, but it also requires expensive hardware and very specialized biomechanical software. The paper describes a methodological procedure to carry out DST analysis with motion data recorded from the Kinect sensor. Specifically, we address the issue to create and interpret angle-angle diagrams with an emphasis on exploring coordination patterns in motion capture (MoCap) signals. We introduced a method to facilitate the DST analysis and we applied it with two different use cases of human movement analysis in real scenarios: sports gesture study and motion analysis in physical rehabilitation interventions. Results showed that important coordination parameters could be deduced from the angle-angle diagrams improving the understanding of motion data when two joints have to be considered. Therefore, we demonstrated that DST analysis could be performed with inexpensive tools providing a promissory approach for coordination and motor synchronization analysis in novel serious games for health.","PeriodicalId":264923,"journal":{"name":"2018 10th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Dynamic Systems Theory in Human Movement Exploring Coordination Patterns by Angle-Angle Diagrams Using Kinect\",\"authors\":\"John Edison Muñoz Cardona, J. F. Villada, S. Casanova, Maria Fernanda Montoya Vega, Ó. Henao\",\"doi\":\"10.1109/VS-Games.2018.8493416\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analyzing time series data using linear spatial/angular kinematics traditionally makes quantification of human movement using low-cost cameras such as the Kinect sensor. Through this conventional approach, interactions between body joints are difficult to analyze and coordination parameters remain hidden. Dynamic Systems Theory (DST) provides a non-linear framework to analyze human movement by representing intersegmental interactions in angle-angle diagrams. DST offers an accurate solution to study coordination in human movement, but it also requires expensive hardware and very specialized biomechanical software. The paper describes a methodological procedure to carry out DST analysis with motion data recorded from the Kinect sensor. Specifically, we address the issue to create and interpret angle-angle diagrams with an emphasis on exploring coordination patterns in motion capture (MoCap) signals. We introduced a method to facilitate the DST analysis and we applied it with two different use cases of human movement analysis in real scenarios: sports gesture study and motion analysis in physical rehabilitation interventions. Results showed that important coordination parameters could be deduced from the angle-angle diagrams improving the understanding of motion data when two joints have to be considered. 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Dynamic Systems Theory in Human Movement Exploring Coordination Patterns by Angle-Angle Diagrams Using Kinect
Analyzing time series data using linear spatial/angular kinematics traditionally makes quantification of human movement using low-cost cameras such as the Kinect sensor. Through this conventional approach, interactions between body joints are difficult to analyze and coordination parameters remain hidden. Dynamic Systems Theory (DST) provides a non-linear framework to analyze human movement by representing intersegmental interactions in angle-angle diagrams. DST offers an accurate solution to study coordination in human movement, but it also requires expensive hardware and very specialized biomechanical software. The paper describes a methodological procedure to carry out DST analysis with motion data recorded from the Kinect sensor. Specifically, we address the issue to create and interpret angle-angle diagrams with an emphasis on exploring coordination patterns in motion capture (MoCap) signals. We introduced a method to facilitate the DST analysis and we applied it with two different use cases of human movement analysis in real scenarios: sports gesture study and motion analysis in physical rehabilitation interventions. Results showed that important coordination parameters could be deduced from the angle-angle diagrams improving the understanding of motion data when two joints have to be considered. Therefore, we demonstrated that DST analysis could be performed with inexpensive tools providing a promissory approach for coordination and motor synchronization analysis in novel serious games for health.