RunningCoach: cadence training system for long-distance runners

D. Aranki, U. Balakrishnan, H. Sarver, Lucas Serven, Carlos Asuncion, Kaidi Du, Caitlin Gruis, Gao Xian Peh, Yu Xiao, R. Bajcsy
{"title":"RunningCoach: cadence training system for long-distance runners","authors":"D. Aranki, U. Balakrishnan, H. Sarver, Lucas Serven, Carlos Asuncion, Kaidi Du, Caitlin Gruis, Gao Xian Peh, Yu Xiao, R. Bajcsy","doi":"10.1145/3154862.3154935","DOIUrl":null,"url":null,"abstract":"Long-distance running is a category of sports that is injury-prone. Half of the injuries sustained in long-distance running are at the knee and are attributed to the inability of the lower extremity joints to sufficiently handle the load applied during initial stance. Furthermore, cadence (steps per minute) has been identified as a factor that is strongly associated with running-related injuries. Increasing cadence results in reduced energy absorption at the hip and the knee, thus reducing the risk of some common running injuries. Therefore, it is vital for runners to run at an appropriate running cadence in order to minimize risk of injury. In this paper, we present an mHealth system that remotely monitors running cadence levels of runners in a continuous fashion, among other variables, and provides immediate feedback to runners in an effort to help them optimize their running cadence. We also present some initial findings based on a feasibility study we are currently conducting using this system.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"132 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3154862.3154935","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Long-distance running is a category of sports that is injury-prone. Half of the injuries sustained in long-distance running are at the knee and are attributed to the inability of the lower extremity joints to sufficiently handle the load applied during initial stance. Furthermore, cadence (steps per minute) has been identified as a factor that is strongly associated with running-related injuries. Increasing cadence results in reduced energy absorption at the hip and the knee, thus reducing the risk of some common running injuries. Therefore, it is vital for runners to run at an appropriate running cadence in order to minimize risk of injury. In this paper, we present an mHealth system that remotely monitors running cadence levels of runners in a continuous fashion, among other variables, and provides immediate feedback to runners in an effort to help them optimize their running cadence. We also present some initial findings based on a feasibility study we are currently conducting using this system.
RunningCoach:长跑运动员节奏训练系统
长跑是一种容易受伤的运动。长跑中有一半的损伤发生在膝盖,这是由于下肢关节无法充分处理初始站立时施加的负荷。此外,节奏(每分钟步数)已被确定为与跑步相关损伤密切相关的一个因素。增加节奏可以减少臀部和膝盖的能量吸收,从而降低一些常见的跑步损伤的风险。因此,对于跑步者来说,以适当的跑步节奏跑步是至关重要的,以尽量减少受伤的风险。在本文中,我们提出了一个移动健康系统,该系统以连续的方式远程监测跑步者的跑步节奏水平,以及其他变量,并为跑步者提供即时反馈,以帮助他们优化跑步节奏。我们还介绍了一些基于我们目前正在使用该系统进行的可行性研究的初步发现。
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