Robert Stanton, Melanie Hayman, Nyree Humphris, Hanna Borgelt, Jordan Fox, Luke Del Vecchio, Brendan Humphries
{"title":"Validity of a Smartphone-Based Application for Determining Sprinting Performance.","authors":"Robert Stanton, Melanie Hayman, Nyree Humphris, Hanna Borgelt, Jordan Fox, Luke Del Vecchio, Brendan Humphries","doi":"10.1155/2016/7476820","DOIUrl":null,"url":null,"abstract":"<p><p>Recent innovations in smartphone technology have led to the development of a number of applications for the valid and reliable measurement of physical performance. Smartphone applications offer a number of advantages over laboratory based testing including cost, portability, and absence of postprocessing. However, smartphone applications for the measurement of running speed have not yet been validated. In the present study, the iOS smartphone application, SpeedClock, was compared to conventional timing lights during flying 10 m sprints in recreationally active women. Independent samples t-test showed no statistically significant difference between SpeedClock and timing lights (t(190) = 1.83, p = 0.07), while intraclass correlations showed excellent agreement between SpeedClock and timing lights (ICC (2,1) = 0.93, p = 0.00, 95% CI 0.64-0.97). Bland-Altman plots showed a small systematic bias (mean difference = 0.13 seconds) with SpeedClock giving slightly lower values compared to the timing lights. Our findings suggest SpeedClock for iOS devices is a low-cost, valid tool for the assessment of mean flying 10 m sprint velocity in recreationally active females. Systematic bias should be considered when interpreting the results from SpeedClock. </p>","PeriodicalId":73953,"journal":{"name":"","volume":"2016 ","pages":"7476820"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2016/7476820","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2016/7476820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2016/7/21 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Recent innovations in smartphone technology have led to the development of a number of applications for the valid and reliable measurement of physical performance. Smartphone applications offer a number of advantages over laboratory based testing including cost, portability, and absence of postprocessing. However, smartphone applications for the measurement of running speed have not yet been validated. In the present study, the iOS smartphone application, SpeedClock, was compared to conventional timing lights during flying 10 m sprints in recreationally active women. Independent samples t-test showed no statistically significant difference between SpeedClock and timing lights (t(190) = 1.83, p = 0.07), while intraclass correlations showed excellent agreement between SpeedClock and timing lights (ICC (2,1) = 0.93, p = 0.00, 95% CI 0.64-0.97). Bland-Altman plots showed a small systematic bias (mean difference = 0.13 seconds) with SpeedClock giving slightly lower values compared to the timing lights. Our findings suggest SpeedClock for iOS devices is a low-cost, valid tool for the assessment of mean flying 10 m sprint velocity in recreationally active females. Systematic bias should be considered when interpreting the results from SpeedClock.