A novel design for automatic measurement of reaction time for audiovisual and muscular stimulus

N. Keerthika., E. Sathish, V. Kiruthika, M. Santhakumar
{"title":"A novel design for automatic measurement of reaction time for audiovisual and muscular stimulus","authors":"N. Keerthika., E. Sathish, V. Kiruthika, M. Santhakumar","doi":"10.1109/ICBSII58188.2023.10181095","DOIUrl":null,"url":null,"abstract":"Reaction Time (RT) is crucial for detecting cognitive abilities in sports and clinical applications. RT Measurements can be used to evaluate the performance and sensory-motor integration of individuals. It determines a person’s attentiveness because RT indicates how rapidly an individual reacts toward a stimulus. A novel experimental setup called Automatic Reaction Time Tester (ARTT) system is proposed in this study to measure the RT using Audio Stimulus (AS), Visual Stimulus (VS), and Muscular Reaction Time (MRT). The ARTT system helps in reducing human intervention and time consumption. It improves accuracy and makes it easier to test the RT in terms of AS, VS, and MRT in a single system. In the sports field, coaches are able to analyze the current condition of the players and modified their training sessions accordingly, Moreover, the individual player can also check their performance through self-diagnosis methods for improving their performance. In the medical field, it assists clinicians in determining a patient’s response to medication and facilitates a speedy recovery through this RT test.","PeriodicalId":388866,"journal":{"name":"2023 International Conference on Bio Signals, Images, and Instrumentation (ICBSII)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Bio Signals, Images, and Instrumentation (ICBSII)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBSII58188.2023.10181095","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

Reaction Time (RT) is crucial for detecting cognitive abilities in sports and clinical applications. RT Measurements can be used to evaluate the performance and sensory-motor integration of individuals. It determines a person’s attentiveness because RT indicates how rapidly an individual reacts toward a stimulus. A novel experimental setup called Automatic Reaction Time Tester (ARTT) system is proposed in this study to measure the RT using Audio Stimulus (AS), Visual Stimulus (VS), and Muscular Reaction Time (MRT). The ARTT system helps in reducing human intervention and time consumption. It improves accuracy and makes it easier to test the RT in terms of AS, VS, and MRT in a single system. In the sports field, coaches are able to analyze the current condition of the players and modified their training sessions accordingly, Moreover, the individual player can also check their performance through self-diagnosis methods for improving their performance. In the medical field, it assists clinicians in determining a patient’s response to medication and facilitates a speedy recovery through this RT test.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种用于自动测量视听和肌肉刺激反应时间的新设计
反应时间(RT)是检测运动认知能力和临床应用的关键。RT测量可用于评估个人的表现和感觉-运动整合。它决定了一个人的注意力,因为RT表明了一个人对刺激的反应有多快。本文提出了一种新的实验装置,称为自动反应时间测试仪(ARTT)系统,该系统使用音频刺激(AS),视觉刺激(VS)和肌肉反应时间(MRT)来测量RT。ARTT系统有助于减少人为干预和时间消耗。它提高了准确性,并使在单个系统中根据AS、VS和MRT测试RT变得更容易。在运动场上,教练员可以分析球员的当前状态,并对训练进行相应的调整,球员个人也可以通过自我诊断的方法来检查自己的表现,从而提高自己的表现。在医学领域,它帮助临床医生确定患者对药物的反应,并通过该RT测试促进快速恢复。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Novel Approach in Web Based 3D Virtualization For Healthcare Infrared Thermograms for Diagnosis of Dry Eye: A Review Resampling-free fast particle filtering with application to tracking rhythmic biomedical signals Parkinson’s Disease Detection And Classification Of Stages From Drawing Patterns Using Deep Learning Analysis Of Raw 3D Images Of Stages Of Alzheimer’s Disease Using Deep Learning
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1