Predictive Simulations of Human Sprinting: Effects of Muscle-Tendon Properties on Sprint Performance

We combined a full-body musculoskeletal model with dynamic optimization theory to predict the biomechanics of maximum-speed sprinting and evaluate the effects of changes in muscle-tendon properties on sprint performance.

The body was modeled as a three-dimensional skeleton actuated by 86 muscle-tendon units. A simulation of jogging was used as an initial guess to generate a predictive dynamic optimization solution for maximum-speed sprinting. Nominal values of lower-limb muscle strength, muscle fascicle length, muscle intrinsic maximum shortening velocity (fiber-type composition), and tendon compliance were then altered incrementally to study the relative influence of each property on sprint performance.

Model-predicted patterns of full-body motion, ground forces, and muscle activations were in general agreement with experimental data recorded for maximum-effort sprinting. Maximum sprinting speed was 1.3 times more sensitive to a change in muscle strength compared with the same change in muscle fascicle length, 2.0 times more sensitive to a change in muscle fascicle length compared with the same change in muscle intrinsic maximum shortening velocity, and 9.1 times more sensitive to a change in muscle intrinsic maximum shortening velocity compared with the same change in tendon compliance. A 10% increase in muscle strength increased maximum sprinting speed by 5.9%, whereas increasing muscle fascicle length, muscle intrinsic maximum shortening velocity, and tendon compliance by 10% increased maximum sprinting speed by 4.7%, 2.4%, and 0.3%, respectively.

Sprint performance was most sensitive to changes in muscle strength and least affected by changes in tendon compliance. Sprint performance was also more heavily influenced by changes in muscle fascicle length than muscle intrinsic maximum shortening velocity. These results could inform training methods aimed at optimizing performance in elite sprinters.