{"title":"Gait Analysis Using Smartwatches","authors":"N. S. Erdem, Cem Ersoy, Can Tunca","doi":"10.1109/PIMRCW.2019.8880821","DOIUrl":null,"url":null,"abstract":"Monitoring gait characteristics is an important tool used in many areas including orthopedics, sports, rehabilitation and neurology. Current methods applied to analyze the gait need clinical settings and equipments for measuring gait parameters. In this study, we propose an unobtrusive and comfortable system to perform gait analysis using smartwatches. Accelerometer and gyroscope sensors of the smartwatch are used to extract three main parameters of gait: step length, swing time and stance time. This study is one of the first smartwatch based gait analysis studies focusing on extracting these spatio-temporal gait parameters. Data is collected from 26 healthy participants in clinical settings. The data is preprocessed and step features are extracted. Gait parameters are estimated using various regression models and compared with the ground truth data coming from the clinician using the golden standard instrumented walkway.","PeriodicalId":158659,"journal":{"name":"2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIMRCW.2019.8880821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Monitoring gait characteristics is an important tool used in many areas including orthopedics, sports, rehabilitation and neurology. Current methods applied to analyze the gait need clinical settings and equipments for measuring gait parameters. In this study, we propose an unobtrusive and comfortable system to perform gait analysis using smartwatches. Accelerometer and gyroscope sensors of the smartwatch are used to extract three main parameters of gait: step length, swing time and stance time. This study is one of the first smartwatch based gait analysis studies focusing on extracting these spatio-temporal gait parameters. Data is collected from 26 healthy participants in clinical settings. The data is preprocessed and step features are extracted. Gait parameters are estimated using various regression models and compared with the ground truth data coming from the clinician using the golden standard instrumented walkway.