{"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.
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使用智能手表进行步态分析
步态特征监测是应用于骨科、运动、康复和神经学等诸多领域的重要工具。目前用于步态分析的方法需要临床环境和测量步态参数的设备。在本研究中,我们提出了一种不显眼且舒适的系统,用于使用智能手表进行步态分析。利用智能手表的加速度计和陀螺仪传感器提取步态的三个主要参数:步长、摆动时间和站立时间。本研究是第一个基于智能手表的步态分析研究,重点是提取这些时空步态参数。数据收集自临床环境中26名健康参与者。对数据进行预处理,提取步长特征。使用各种回归模型估计步态参数,并与使用黄金标准器械步行的临床医生提供的真实数据进行比较。
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