Validation of Whole-Body COM Movement from 3D Anthropometric Image with Dynamic Data at Different Human Standard MVJ

Abstract

This study presents and applies noninvasive subject specific validation of human whole-body (WB) center of mass (COM) kinematic from 3D anthropometric multibody model using dynamic data from ground reaction forces during impulse phase at standard maximum vertical jump (MVJ) with long countermovement (CM) on countermovement jump (CMJ) and short CM on drop jump (DJ) for comparison with MVJ without CM on squat jump (SJ), assessing lower limb CM contribution and muscle stretch-shortening cycle (SSC) at WB COM vertical impulse. A small group of n = 6 sports and physical education degree students with (21.5 ± 1.4) years old, without previous injuries, specific sport abilities or train were weighed (76.7 ± 9.3) kg and their height measured (1.79 ± 0.06) m. Adhesive reflective marks were attached at main upper and lower limb joints. Each subject performed a total of 3 trial at each MVJ, CMJ, DJ and SJ. During trial tests kinematics of anatomical points were registered with two JVC GR-VL9800 digital video cameras at 100 Hz and ground reaction forces with AMTI platform model BP2416-4000 CE operating at 1000 Hz. WB COM kinematics was determined using calibrated SIMI motion tracking of joint reflective marks and Dempster model selecting vertical WB COM displacement Δzk according to higher amplitude and research interest on MVJ WB COM movement for CM and SSC assessment. Dynamic of WB COM vertical displacement Δzd was determined from double time integration of COM vertical acceleration. Comparison of kinematic Δzk and dynamic Δzd was statistically tested on average and variance at each MVJ type, Δzk with Δzd and on root mean square-error (RMSE) during impulse phase. Results present similar variability of Δzk and Δzd at each MVJ p > 0.05, with mean values discriminating CMJ different means p < 0.05 from DJ and SJ with equal means p > 0.05, pointing dynamic data as suitable for validation of WB COM movement from 3D anthropometric image as well as for detection of different RMSE at each type of MVJ, its influence on assessment of CM and SSC and improve accuracy on kinematic, dynamic measurements and models.