Optimising muscle parameters in musculoskeletal models using Monte Carlo simulation

Abstract

The use of musculoskeletal simulation software has become a useful tool for modelling joint and muscle forces during human activity, including in reduced gravity because direct experimentation is difficult. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler™ (San Clemente, CA, USA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces but no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. The rectus femoris was predicted to peak at 60.1% activation in the same test case compared to 19.2% activation using default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.

Towards human exploration of space: the THESEUS review series on muscle and bone research priorities

“…In addition to the type of physical activity, further individual variation is associated with spacesuit design. Development of computational 69, 70 and experimental techniques 71, 72 to respectively predict and measure the loads exerted on bone, muscle and cartilage across the range of physical activities, and spacesuit designs is essential both to understanding the potential protective effect of EVA activities on the musculoskeletal system as well as to identify variants of exercise and EVA activities that may result in injury. To this end, the development of vertical treadmill systems 73 and lower body negative pressure systems 74 has been instrumental to understanding how variations of load under partial gravity may provide different degrees of osteoprotection and protection against muscle loss.…”

Neck musculoskeletal model generation through anthropometric scaling

“…Such a neck model has been developed by Suderman et al [23,38,39],but they cautioned that the model can be very sensitive to wrapping object or via point kinematics and inter-individual differences in muscle paths and joint kinematics. Several studies in literature have performed comparable muscle parameter optimization studies [40][41][42]. Some used Monte Carlo methods to match muscle activation during a particular movement [41,42] and compared whether muscle parameters were within physiological limits after the optimizations.…”

“…Several studies in literature have performed comparable muscle parameter optimization studies [40][41][42]. Some used Monte Carlo methods to match muscle activation during a particular movement [41,42] and compared whether muscle parameters were within physiological limits after the optimizations. Others explored the effects of measurement errors during experimental data collection and parameter estimation during inverse kinematics and dynamics Table 5.…”

Neck Musculoskeletal Model Generation through Anthropometric Scaling

“…Several studies in literature have performed comparable muscle parameter optimization studies (40–42). Some used Monte Carlo methods to match muscle activation during a particular movement (41, 42) and compared whether muscle parameters were within physiological limits after the optimizations. Others explored the effects of measurement errors during experimental data collection and parameter estimation during inverse kinematics and dynamics (40).…”