Countermovement jump and squat jump force-time curve analysis in control and fatigue conditions

Authors

Steven Hughes, Edith Cowan UniversityFollow
John Warmenhoven
G. Gregory Haff, Edith Cowan UniversityFollow
Dale W. Chapman, Edith Cowan UniversityFollow
Sophia Nimphius, Edith Cowan UniversityFollow

Author Identifier

Steven Hughes

https://orcid.org/0000-0001-8020-9856

Guy Gregory Haff

https://orcid.org/0000-0002-0676-7750

Dale Chapman

https://orcid.org/0000-0002-3393-1261

Sophia Nimphius

https://orcid.org/0000-0002-3524-0245

Document Type

Journal Article

Publication Title

Journal of Strength and Conditioning Research

Publisher

Wolters Kluwer

School

Centre for Exercise and Sports Science Research / School of Medical and Health Sciences

RAS ID

35932

Funders

Edith Cowan University - Open Access Support Scheme 2020

Comments

Hughes, S., Warmenhoven, J., Haff, G.G., Chapman, D.W., Nimphius, S. (2022). Countermovement jump and squat jump force-time curve analysis in control and fatigue conditions. Journal of Strength and Conditioning Research, 36(10), 2752-2761.

https://doi.org/10.1519/JSC.0000000000003955

Abstract

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.

DOI

10.1519/JSC.0000000000003955

Related Publications

Hughes, S. (2023). The use of performance assessments and force-time curve analysis to measure mental and physical fatigue. https://ro.ecu.edu.au/theses/2643

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.