Predictive musculoskeletal simulation using optimal control: effects of added limb mass on energy cost and kinematics of walking and running

When designing sports equipment, it is often desirable to predict how certain design parameters will affect human performance. In many instances, this requires a consideration of human musculoskeletal mechanics and adaptive neuromuscular control. Current computational methods do not represent these mechanisms, and design optimization typically requires several iterations of prototyping and human testing. This paper introduces a computational method based on musculoskeletal modeling and optimal control, which has the capability to predict the effect of mechanical equipment properties on human performance. The underlying assumption is that users will adapt their neuromuscular control according to an optimality principle, which balances task performance with a minimization of muscular effort. The method was applied to the prediction of metabolic cost and limb kinematics while running and walking with weights attached to the body. A two-dimensional musculoskeletal model was used, with nine kinematic degrees of freedom and 16 muscles. The optimal control problem was solved for two walking speeds and two running speeds, and at each speed, with 200 g and 400 g masses placed at the thigh, knee, shank and foot. The model predicted an increase in energy expenditure that was proportional to the added mass and the effect was largest for a mass placed on the foot. Specifically, the model predicted an energy cost increase of 0.74% for each 100 g mass added to the foot during running at 3.60 m/s. The model also predicted that stride length would increase by several millimetres in the same condition, relative to the model without added mass. These predictions were consistent with previously published human studies. Peak force and activation remained the same in most muscles, but increased by 26% in the hamstrings and by 17% in the rectus femoris for running at 4.27 m/s with 400 g added mass at the foot, suggesting muscle-specific training effects. This work demonstrated that a musculoskeletal model with optimal control can predict the effect of mechanical devices on human performance, and could become a useful tool for design optimization in sports engineering. The theoretical background of predictive simulation also helps explain why human athletes have specific responses when exercising in an altered mechanical environment

Ontogenetic allometry and architectural properties of the paravertebral and hindlimb musculature in Eastern cottontail rabbits (Sylvilagus floridanus): functional implications for developmental changes in locomotor performance

Due to small body size, an immature musculoskeletal system, and other growth‐related limits on performance, juvenile mammals frequently experience a greater risk of predation than their adult counterparts. As a result, behaviorally precocious juveniles are hypothesized to exhibit musculoskeletal advantages that permit them to accelerate rapidly and evade predation. This hypothesis was tested through detailed quantitative evaluation of muscle growth in wild Eastern cottontail rabbits (Sylvilagus floridanus). Cottontail rabbits experience high rates of mortality during the first year of life, suggesting that selection might act to improve performance in growing juveniles. Therefore, it was predicted that muscle properties associated with force and power capacity should be enhanced in juvenile rabbits to facilitate enhanced locomotor performance. We quantified muscle architecture from 24 paravertebral and hindlimb muscles across ontogeny in a sample of n = 29 rabbits and evaluated the body mass scaling of muscle mass (MM), physiological cross‐sectional area (PCSA), isometric force (F (max)), and instantaneous power (P (inst)), along with several dimensionless architectural indices. In contrast to our hypothesis, MM and PCSA for most muscles change with positive allometry during growth by scaling at [Formula: see text] and [Formula: see text] , respectively, whereas F (max) and P (inst) generally scale indistinguishably from isometry, as do the architectural indices tested. However, scaling patterns indicate that the digital flexors and ankle extensors of juvenile S. floridanus have greater capacities for force and power, respectively, than those in adults, suggesting these muscle properties may be a part of several compensatory features that promote enhanced acceleration performance in young rabbits. Overall, our study implies that body size constraints place larger, more mature rabbits at a disadvantage during acceleration, and that adults must develop hypertrophied muscles in order to maintain mechanical similarity in force and power capacities across development. These findings challenge the accepted understanding that juvenile animals are at a performance detriment relative to adults. Instead, for prey–predator interactions necessitating short intervals of high force and power generation relative to body mass, as demonstrated by rapid acceleration of cottontail rabbits fleeing predators, it may be the adults that struggle to keep pace with juveniles