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Countermovement Jump and Squat Jump Force-Time Curve Analysis in Control and Fatigue Conditions
Steven Hughes1,2, John Warmenhoven3, G Gregory Haff2
1New South Wales Institute of Sport, Sydney Olympic Park, New South Wales, Australia.
Abstract:
Hughes, S, Warmenhoven, J, Haff, GG, Chapman, DW, and Nimphius, S. Countermovement jump and squat jump force-time curve analysis in control and fatigue conditions. J Strength Cond Res 36(10): 2752-2761, 2022-This study aimed to reanalyze previously published discrete force data from countermovement jumps (CMJs) and squat jumps (SJs) using statistical parametric mapping (SPM), a statistical method that enables analysis of data in its native, complete state. Statistical parametric mapping analysis of 1-dimensional (1D) force-time curves was compared with previous zero-dimensional (0D) analysis of peak force to assess sensitivity of 1D analysis. Thirty-two subjects completed CMJs and SJs at baseline, 15 minutes, 1, 24, and 48 hours following fatigue and control conditions in a pseudo random cross-over design. Absolute (CMJ ABS /SJ ABS ) and time-normalized (CMJ NORM /SJ NORM ) force-time data were analyzed using SPM 2-way repeated measures analysis of variance with significance accepted at α = 0.05. The SPM indicated a magnitude of difference between force-time data with main effects for time ( p < 0.001) and interaction ( p < 0.001) observed in CMJ ABS , SJ ABS, and SJ NORM, whereas previously published 0D analysis reported no 2-way interaction in CMJ and SJ peak force. This exploratory research demonstrates the strength of SPM to identify changes between entire movement force-time curves. Continued development and use of SPM analysis techniques could present the opportunity for refined assessment of athlete fatigue and readiness with the analysis of complete force-time curves.
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