Using wrist-worn sensors to measure and compare physical activity changes for patients undergoing rehabilitation

J. Dahmen, Alyssa La Fleur, Gina Sprint, D. Cook, D. Weeks
{"title":"Using wrist-worn sensors to measure and compare physical activity changes for patients undergoing rehabilitation","authors":"J. Dahmen, Alyssa La Fleur, Gina Sprint, D. Cook, D. Weeks","doi":"10.1109/PERCOMW.2017.7917643","DOIUrl":null,"url":null,"abstract":"Wrist-worn sensors have increased in popularity in health care settings. As the use of wrist-worn sensors increases, a better understanding is needed of how to detect changes in behavior as well as an ability to quantify such changes. We introduce a statistical method to address this need. In this study, we used Fitbit Charge Heart Rate devices with two separate populations to continuously record data. There were eight participants in the healthy control group and nine in the hospitalized inpatient rehabilitation group. We performed comparisons both within the groups and between groups on the gathered step count and heart rate data. The inpatient rehabilitation group showed improved step count changes between the first half of the study participation and the second half. Heart rate did not show significant changes for either the healthy control group or inpatient rehabilitation group across time. We conclude that our statistical change analysis applied to wrist-worn sensors can effectively detect changes in physical activity that provides valuable information to patients as well as their healthcare care providers.","PeriodicalId":319638,"journal":{"name":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","volume":"1962 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERCOMW.2017.7917643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

Wrist-worn sensors have increased in popularity in health care settings. As the use of wrist-worn sensors increases, a better understanding is needed of how to detect changes in behavior as well as an ability to quantify such changes. We introduce a statistical method to address this need. In this study, we used Fitbit Charge Heart Rate devices with two separate populations to continuously record data. There were eight participants in the healthy control group and nine in the hospitalized inpatient rehabilitation group. We performed comparisons both within the groups and between groups on the gathered step count and heart rate data. The inpatient rehabilitation group showed improved step count changes between the first half of the study participation and the second half. Heart rate did not show significant changes for either the healthy control group or inpatient rehabilitation group across time. We conclude that our statistical change analysis applied to wrist-worn sensors can effectively detect changes in physical activity that provides valuable information to patients as well as their healthcare care providers.
使用腕戴式传感器测量和比较康复患者的身体活动变化
腕戴式传感器在医疗保健领域越来越受欢迎。随着腕戴式传感器使用的增加,需要更好地了解如何检测行为变化以及量化这种变化的能力。我们引入了一种统计方法来解决这一需求。在这项研究中,我们使用Fitbit充电心率设备与两个不同的人群连续记录数据。健康对照组8人,住院康复组9人。我们对组内和组间收集的步数和心率数据进行了比较。住院康复组在参与研究的前半段和后半段之间的步数变化有所改善。无论是健康对照组还是住院康复组,心率都没有随时间的显著变化。我们的结论是,我们的统计变化分析应用于腕戴式传感器可以有效地检测身体活动的变化,为患者及其医疗保健提供者提供有价值的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信