Errors in Predicting Muscle Fiber Lengths from Joint Kinematics Point to the Need to Include Tendon Tension in Computational Neuromuscular Models

Abstract

Accurate predictions of tendon forces must consider musculotendon mechanics; specifically muscle fiber lengths and velocities. These are either predicted explicitly by simulating musculoskeletal dynamics or approximated from measured limb kinematics. The latter is complicated by the fact that tendon lengths and pennation angles vary with both limb kinematics and tendon tension. We now derive the error in kinematically-approximated muscle fiber lengths as a general equation of muscle geometry and tendon tension. This enables researchers to objectively evaluate this error’s significance—which can reach ~ 80% of the optimal muscle fiber length—with respect to the scientific or clinical question being asked. Although this equation provides a detailed functional relationship between muscle fiber lengths, joint kinematics and tendon tension, the parameters used to characterize musculotendon architecture are subject- and muscle-specific. This parametric uncertainty limits the accuracy of any generic musculoskeletal model that hopes to explain subject-specific phenomena. Nevertheless, the existence of such a functional relationship has profound implications to biological proprioception. These results strongly suggest that tendon tension information (from Golgi tendon organs) is likely integrated with muscle fiber length information (from muscle spindles) at the spinal cord to produce useful estimates of limb configuration to enable effective control of movement.