{"title":"A feasibility study of using a single Kinect sensor for rehabilitation exercises monitoring: A rule based approach","authors":"Wenbing Zhao, D. Espy, M. A. Reinthal, Hai Feng","doi":"10.1109/CICARE.2014.7007827","DOIUrl":null,"url":null,"abstract":"In this paper, we present a feasibility study for using a single Microsoft Kinect sensor to assess the quality of rehabilitation exercises. Unlike competing studies that have focused on the validation of the accuracy of Kinect motion sensing data at the level of joint positions, joint angles, and displacement of joints, we take a rule based approach. The advantage of our approach is that it provides a concrete context for judging the feasibility of using a single Kinect sensor for rehabilitation exercise monitoring. Our study aims to answer the following question: if it is found that Kinect's measurement on a metric deviates from the ground truth by some amount, is this an acceptable error? By defining a set of correctness rules for each exercise, the question will be answered definitively with no ambiguity. Defining appropriate context in a validation study is especially important because (1) the deviation of Kinect measurement from the ground truth varies significantly for different exercises, even for the same joint, and (2) different exercises have different tolerance levels for the movement restrictions of body segments. In this study, we also show that large but systematic deviations of the Kinect measurement from the ground truth are not as harmful as it seems because the problem can be overcome by adjusting parameters in the correctness rules.","PeriodicalId":120730,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"52","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICARE.2014.7007827","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 52
Abstract
In this paper, we present a feasibility study for using a single Microsoft Kinect sensor to assess the quality of rehabilitation exercises. Unlike competing studies that have focused on the validation of the accuracy of Kinect motion sensing data at the level of joint positions, joint angles, and displacement of joints, we take a rule based approach. The advantage of our approach is that it provides a concrete context for judging the feasibility of using a single Kinect sensor for rehabilitation exercise monitoring. Our study aims to answer the following question: if it is found that Kinect's measurement on a metric deviates from the ground truth by some amount, is this an acceptable error? By defining a set of correctness rules for each exercise, the question will be answered definitively with no ambiguity. Defining appropriate context in a validation study is especially important because (1) the deviation of Kinect measurement from the ground truth varies significantly for different exercises, even for the same joint, and (2) different exercises have different tolerance levels for the movement restrictions of body segments. In this study, we also show that large but systematic deviations of the Kinect measurement from the ground truth are not as harmful as it seems because the problem can be overcome by adjusting parameters in the correctness rules.