(D-158) ANALYSIS OF ANKLE JOINT LOADING RATE IN DROP JUMPS FOR BONE ADAPTATION

Overuse injuries in the distal tibia are common, especially in athletes [1]. As bones resorb and form, there is an increased risk for overuse and bone stress injuries. A vital part of understanding tibial bone stress injuries is estimating ankle loading as an indication of bone adaptation. While there is research analyzing tibial bone loading in running [2], a better understanding of bone loading in plyometric activities, which are shown to increase bone strength, is needed [3]. By investigating the tibial loading on drop jumps, a plyometric activity, we can begin to understand how to perform the exercise to build bone strength and simultaneously avoid bone stress injuries. This study calculated the loading rate based on the ankle joint contact force (JCF) to categorize the trials into two landing types: high impact and low impact landings. JCF must be predicted using ex vivo data, so computational modeling was used to predict the contributions of muscle actuators with model constraints. The study aims to compare loading rates in high and low impact groups to their ankle angle at landing between unilateral and bilateral drop jumps. Observing the angle of the ankle joint at landing between the two impact groups can allow for an adaptation of exercise to improve bone strength based on landing style. We hypothesized that the high impact group will show dorsiflexion and the low impact group will show plantarflexion of the ankle during landing.

Motion capture data were gathered on 12 healthy adults (4 male, 8 female, 21.3 +/- 2.5 years), uninjured over the prior six months, executing drop jump trials from 0.2, 0.4, 0.5, and 0.6 meters each with a bilateral and unilateral landing. The trial data were collected using Vicon Motion Capture (Vicon Motion Systems Ltd, UK) at 100 Hz, using an adapted full-body plug-in gait marker set and 1000 Hz force plates (AMTI, Watertown, MA). A skeletal model was adapted with Visual3D (C-Motion, Inc., Germantown, MD). Then, a lower extremity and torso model (gait2392 model; Rajagopal et al. 2015) was scaled by participant mass and used to obtain ankle JCF in OpenSim 4.4 (Delp SL. et al. 2007) from compatible Visual3D exports. We used inverse dynamics to obtain forces and moments at joints, then static optimization to calculate muscle activation and equilibrium states at each time frame, and joint reaction analysis, resulting in ankle JCF data. The ankle JCF was normalized by body weight and processed through a lowpass Butterworth filter with a cutoff frequency of 6Hz and plotted in Figure 1. The loading rate was calculated by deriving ankle JCF, recording the minimum of the derivative, and taking the absolute value using MATLAB (The MathWorks Inc., Natick, MA). The drop jump loading rates were rank ordered and sorted into four groups: bilateral low impact (BL-LI), bilateral high impact (BL-HI), unilateral low impact (UL-LI), and unilateral high impact (UL-HI).

JCF was obtained for a total of 126 bilateral and 80 unilateral drop jumps. The average and standard deviation of loading rate and ankle angle at landing are reported in Table 1. A positive angle is dorsiflexed and negative is plantarflexed. Unpaired, equal variance t-test were performed between BL-LI and BL-HI ankle angles as well as UL-LI and UL-HI at a significance of α=0.05, resulting in p <0.001 for bilateral and p = 0.037 for unilateral. Based on the p-values, landing with greater dorsiflexion is associated with the higher impact groups as visualized in Figure 2, supporting the hypothesis. The trends hold for both bilateral and unilateral landings, as summarized in Figure 3. A post hoc analysis found that drop height had no effect on loading rate in the bilateral nor the unilateral landings (BL p=0.276; UL p=0.186 from a one-way ANOVA). Only 2 trials in the UL-HI and 0 out of 54 total of UL-LI landed with dorsiflexion. One source of limitation is that we did not use OpenSim’s Residual Reduction Algorithm tool because of its dependency on the ground reaction force data throughout the trial. These results indicate that drop jump exercises can be adapted to achieve higher ankle loading rates by changing the ankle angle at landing and not the height of a drop jump. Overall, we saw that the bone health benefit of plyometric activities is not limited to the intensity of the exercise but rather how the exercise is performed.

This work was supported by NSF REU grant EEC2150076.

[1] Sanderlin BW, Raspa RF. Common stress fractures. Am Fam Physician. 2003;68(8):1527-1532.
[2] Sasimontonkul S, Bay BK, Pavol MJ. Bone contact forces on the distal tibia during the stance phase of running. J Biomech. 2007;40(15):3503-3509. doi:10.1016/j.jbiomech.2007.05.024
[3] Witzke KA, Snow CM. Effects of plyometric jump training on bone mass in adolescent girls. Med Sci Sports Exerc. 2000;32(6):1051-1057. doi:10.1097/00005768-200006000-00003
[4] Santello M. Review of motor control mechanisms underlying impact absorption from falls. Gait & Posture. 2005;21(1):85-94. doi:10.1016/j.gaitpost.2004.01.005