Date of Award

5-2021

Degree Type

Report

Degree Name

Master of Science (MS)

Department

Kinesiology and Health Science

Committee Chair(s)

Talin Louder (Committee Chair)

Committee

Talin Louder

Committee

Brennan Thompson

Committee

Eadric Bressel

Abstract

Greater lower extremity stiffness has been shown to increase bilateral jump height through stretch-shortening cycle optimization. Currently, there are two established methods for estimating vertical stiffness (Kvert) of the human body, which is a variant of lower extremity stiffness. The validity of these methods for estimating Kvert in non-cyclical human movements has been questioned recently due to the complex physiological and neuromotor factors that support stiffness regulation in the muscle-tendon complex. The purpose of the present study was to improve the specificity of Kvert measurement using direct derivation of vertical ground reaction force (GRF) and center of mass displacement (dCoM) data that correspond with the landing phase of depth jumping (DJ). Twenty NCAA Division I basketball athletes (male = 9, female = 11; age = 19.9 ± 1.1 years; mass = 82.6 ± 13.9 kg; height = 188.6 ± 11.3 cm) attended a single data collection session. Participants performed three successful trials of depth jumps (DJ) from drop heights of 0.51m, 0.66m, and 0.81m. DJ performance was measured using 2-dimensional video recordings and force platform dynamometry. Kvert was estimated using conventional methods as a ratio of maximum GRF to either dCoM corresponding to the time point of maximum GRF (Kvert1) or maximum dCoM displacement (Kvert2). GRF and dCoM data were then interpolated using a Lagrange polynomial, yielding 1000 equally spaced data points in the dCoM domain. Interpolated data were passed through a Savistky-Golay polynomial filter. Following interpolation, Kvert1 and Kvert2 were estimated a second time to evaluate for signal distortion. The new estimation method (KvertNew) was then calculated through first central difference derivation of interpolated GRF data with respect to interpolated dCoM data. Simple linear regression models were fit to GRF and dCoM data using Kvert1 and Kvert2 values. The validity of Kvert1 and Kvert2 was evaluated using Root Mean Square Error (RMSE) and coefficients of determination (R2) returned from the linear models. Segmented linear regression was then fit to interpolated GRF and dCoM data. The validity of KvertNew was evaluated using RMSE and R2 values returned from the segmented linear models. One-way repeated measures ANOVAs were conducted to evaluate for main effects of estimation method on Kvert, RMSE, and R2. Post-hoc comparisons were made using Bonferroni-adjusted paired t-tests. There were significant main effects of estimation method on Kvert (p p R2 values (p vert1 and Kvert2 were significantly lower than peak KvertNew (p vertNew (p vert1 and Kvert2 were not affected by the interpolation technique (p = 1.0). RMSE values were significantly greater for Kvert1 and Kvert2 when compared with KvertNew. R2 values returned from the segmented linear models were significantly greater than values returned from the simple linear models constructed using Kvert1 and Kvert2 data. KvertNew appears to be a feasible method for estimating Kvert in DJ landings. KvertNew may also provide greater specificity and address the threats to validity associated with conventional estimation methods.

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