Heart Rate Estimation in Sports Based on Multi-Sensor Data for Sports Intensity Prediction

Feng Zhang
{"title":"Heart Rate Estimation in Sports Based on Multi-Sensor Data for Sports Intensity Prediction","authors":"Feng Zhang","doi":"10.4018/ijdst.307990","DOIUrl":null,"url":null,"abstract":"The heart rate (HR) is the most common measurement of the cardiovascular system. It reflects not only the cardiovascular function, but also the degree of recovery, and has high reliability. The heart rate monitoring can be used in athlete selection, sports training, medical supervision, and fitness to avoid the blindness of exercise intensity arrangement, provide an objective quantitative standard for scientific fitness, and improve the sports performance through monitoring sports intensity. In order to accurately predict the sports intensity, this paper adopts ECG signals and pulse wave to learn an ordinal regression model that can utilize the order relation between different sports intensity level. The experimental results have demonstrated the effectiveness of the proposed sports intensity method.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Distributed Syst. Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijdst.307990","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The heart rate (HR) is the most common measurement of the cardiovascular system. It reflects not only the cardiovascular function, but also the degree of recovery, and has high reliability. The heart rate monitoring can be used in athlete selection, sports training, medical supervision, and fitness to avoid the blindness of exercise intensity arrangement, provide an objective quantitative standard for scientific fitness, and improve the sports performance through monitoring sports intensity. In order to accurately predict the sports intensity, this paper adopts ECG signals and pulse wave to learn an ordinal regression model that can utilize the order relation between different sports intensity level. The experimental results have demonstrated the effectiveness of the proposed sports intensity method.
基于多传感器数据的运动心率估计及运动强度预测
心率(HR)是心血管系统最常用的测量方法。既能反映心血管功能,又能反映恢复程度,可靠性高。心率监测可应用于运动员选拔、运动训练、医疗监护、健身等方面,避免运动强度安排的盲目性,为科学健身提供客观的定量标准,通过监测运动强度提高运动成绩。为了准确预测运动强度,本文采用心电信号和脉搏波学习一种利用不同运动强度水平之间的顺序关系的有序回归模型。实验结果证明了运动强度法的有效性。
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