Muscle Tension Estimation in the Presence of Neuromuscular Impairment

Abstract

Static optimization approaches to estimating muscle tensions rely on the assumption that the muscle activity pattern is in some sense optimal. However, in the case of individuals with a neuromuscular impairment, this assumption is likely not to hold true. We present an approach to muscle tension estimation that does not rely on any optimality assumptions. First, the nature of the impairment is estimated by reformulating the relationship between the muscle tensions and the external forces produced in terms of the deviation from the expected activation in the unimpaired case. This formulation allows the information from several force production tasks to be treated as a single coupled system. In a second step, the identified impairments are used to obtain a novel cost function for the muscle tension estimation task. In a simulation study of the index finger, the proposed method resulted in muscle tension errors with a mean norm of 23.3 ± 26.8% (percentage of the true solution norm), compared to 52.6 ± 24.8% when solving the estimation task using a cost function consisting of the sum of squared muscle stresses. Performance was also examined as a function of the amount of error in the kinematic and muscle Jacobians and found to remain superior to the performance of the squared muscle stress cost function throughout the range examined.