Simulated cycling data set and musculoskeletal models

This study used musculoskeletal modelling to explore the relationship
between cycling conditions (power output and cadence) and muscle
activation and metabolic power. We hypothesized that the cadence that
minimized the simulated average active muscle volume would be higher than
that which minimized the simulated metabolic power. We validated the
simulation by comparing predicted muscle activation and fascicle
velocities with experimental electromyography and ultrasound images. We
found strong correlations for averaged muscle activations and moderate to
good correlations for fascicle dynamics. These correlations tended to
weaken when analyzed at the individual participant level. Our study
revealed a curvilinear relationship between average active muscle volume
and cadence, with the minimum active volume being aligned to the
self-selected cadence. The simulated metabolic power was consistent with
previous results and was minimized at lower cadences than that which
minimized active muscle volume across power outputs. Whilst there are some
limitations to the musculoskeletal modelling approach, the findings
suggest that minimizing active muscle volume may be a more important
factor than minimizing metabolic power for self-selected cycling cadence
preferences. Further research is warranted to explore the potential of an
active muscle volume-based objective function for control schemes across a
wider range of cycling conditions.