Henryk Josiński, P. Grabiec, Magdalena Pawlyta, K. Wojciechowski, A. Świtoński, A. Michalczuk
{"title":"基于CAREN扩展系统的老年人步态混沌行为分析","authors":"Henryk Josiński, P. Grabiec, Magdalena Pawlyta, K. Wojciechowski, A. Świtoński, A. Michalczuk","doi":"10.1109/HealthCom.2018.8531131","DOIUrl":null,"url":null,"abstract":"The aim of this study was to analyze the presence of chaotic behaviors in gait of elderly subjects (‘65+’) by means of the largest short-term Lyapunov exponent computed for six scenarios which differed with respect to ground inclination, walking speed and optional external perturbation. The largest Lyapunov exponent quantifies the amount of chaos in a time series. The bigger positive Lyapunov exponent value, the greater system’s sensitivity to infinitesimal changes in initial conditions at the beginnings of successive gait cycles and, thus, a chaotic behavior during walking. The time series representing the joint angles of ankle, knee and hip joints were recorded in the CAREN Extended environment using the motion capture technique. Data collected for respective joints were grouped forming for each joint a multivariate time series – input data for calculation of the largest Lyapunov exponent.","PeriodicalId":232709,"journal":{"name":"2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Analysis of Chaotic Behaviors in Gait of the Elderly using the CAREN Extended System\",\"authors\":\"Henryk Josiński, P. Grabiec, Magdalena Pawlyta, K. Wojciechowski, A. Świtoński, A. Michalczuk\",\"doi\":\"10.1109/HealthCom.2018.8531131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this study was to analyze the presence of chaotic behaviors in gait of elderly subjects (‘65+’) by means of the largest short-term Lyapunov exponent computed for six scenarios which differed with respect to ground inclination, walking speed and optional external perturbation. The largest Lyapunov exponent quantifies the amount of chaos in a time series. The bigger positive Lyapunov exponent value, the greater system’s sensitivity to infinitesimal changes in initial conditions at the beginnings of successive gait cycles and, thus, a chaotic behavior during walking. The time series representing the joint angles of ankle, knee and hip joints were recorded in the CAREN Extended environment using the motion capture technique. Data collected for respective joints were grouped forming for each joint a multivariate time series – input data for calculation of the largest Lyapunov exponent.\",\"PeriodicalId\":232709,\"journal\":{\"name\":\"2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HealthCom.2018.8531131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HealthCom.2018.8531131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Chaotic Behaviors in Gait of the Elderly using the CAREN Extended System
The aim of this study was to analyze the presence of chaotic behaviors in gait of elderly subjects (‘65+’) by means of the largest short-term Lyapunov exponent computed for six scenarios which differed with respect to ground inclination, walking speed and optional external perturbation. The largest Lyapunov exponent quantifies the amount of chaos in a time series. The bigger positive Lyapunov exponent value, the greater system’s sensitivity to infinitesimal changes in initial conditions at the beginnings of successive gait cycles and, thus, a chaotic behavior during walking. The time series representing the joint angles of ankle, knee and hip joints were recorded in the CAREN Extended environment using the motion capture technique. Data collected for respective joints were grouped forming for each joint a multivariate time series – input data for calculation of the largest Lyapunov exponent.