Kap-Ho Seo, Yongsik Park, Sungjo Yun, Sung-Ho Park, Jungsoo Jun, Kwang-Woo Jeon
{"title":"Gait pattern generation for gait rehabilitation","authors":"Kap-Ho Seo, Yongsik Park, Sungjo Yun, Sung-Ho Park, Jungsoo Jun, Kwang-Woo Jeon","doi":"10.1109/URAI.2013.6677388","DOIUrl":null,"url":null,"abstract":"Robotic gait rehabilitation devices enable efficient and convenient gait rehabilitation by mimicking the functions of physical theraphists. In manual gait rehabilitation training, physical theraphists have patients practice and memorize normal gait patterns by applying assistive torque to the patient's joint once the patient's gait deviates from the normal gait. Thus, one of the most important factors in robotic gait rehabilitation devices is to determine the assistive torque to the patient's joint during rehabilitation training. In order to calculate the assistive torque, the desired gait trajectory for affected leg should be determined. This reference trajectory is obtained from his healthy leg. The obtained signal has many noisy factors. Therefore, after conditioning the signal, the suitable pattern is applied to the developed system. This procedure is called “gait pattern generation” in this paper. It is described and discussed in detail.","PeriodicalId":431699,"journal":{"name":"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URAI.2013.6677388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Robotic gait rehabilitation devices enable efficient and convenient gait rehabilitation by mimicking the functions of physical theraphists. In manual gait rehabilitation training, physical theraphists have patients practice and memorize normal gait patterns by applying assistive torque to the patient's joint once the patient's gait deviates from the normal gait. Thus, one of the most important factors in robotic gait rehabilitation devices is to determine the assistive torque to the patient's joint during rehabilitation training. In order to calculate the assistive torque, the desired gait trajectory for affected leg should be determined. This reference trajectory is obtained from his healthy leg. The obtained signal has many noisy factors. Therefore, after conditioning the signal, the suitable pattern is applied to the developed system. This procedure is called “gait pattern generation” in this paper. It is described and discussed in detail.