Validity and Reliability of a Computer Vision System to Determine Bar Displacement and Velocity

Autor: Christopher Taber, Emma Patterson, Jui Shah, Padraig Francis, Justin Wager
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: International Journal of Strength and Conditioning, Vol 3, Iss 1 (2023)
Druh dokumentu: article
ISSN: 2634-2235
DOI: 10.47206/ijsc.v3i1.263
Popis: This study examined the validity and reliability of a video-based smartphone application (VBA) to measure displacement and velocity in the barbell bench press, back squat, and deadlift. Nine resistance-trained subjects (three females; six males; age: 24.2±4.2 years; height 175.8±8.1 cm; body mass 87.2±18.2kg) completed two test-retest sessions for the barbell bench press, back squat, and deadlift one week apart. Eight repetitions were completed for the bench press, back squat, and deadlift with a load of 40kg and completed at fast and slow velocities. Bar displacement and average velocity were measured simultaneously using 3-D motion capture (MC) and a VBA. The VBA’s validity and reliability were analyzed by Pearson’s product-moment correlation coefficient (r), intraclass correlation coefficient (ICC), and Bland-Altman Plots. Displacement data showed moderate to nearly perfect correlations (r =0.43-0.94) and moderate to excellent reliability (ICC= 0.67-0.98) and Bland-Altman plots revealing little bias (< 2cm). Average velocity data showed large to nearly perfect correlations (r =0.67-0.95) and good to excellent reliability (ICC= 0.79-0.94) with Bland-Altman revealing little bias (< 0.06 m/s). Taken together the VBA examined in this study was both valid and reliable compared with a gold standard criterion measurement of MC. These results provide evidence that the VBA may be used in the tracking of displacement and average velocity in the bench press, back squat, and deadlift at both fast and slower movement velocities.
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