Mathematical model that predicts lower leg motion in response to electrical stimulation

Electrical stimulation of skeletal muscles of patients with upper motor neuron lesions can be used to restore functional movements such as standing or walking. Mathematical muscle models can assist in designing stimulation patterns that will enable patients to perform particular tasks more efficiently. In this study we extend our previous model to allow us to predict changes in knee joint angle in response to electrical stimulation of the human quadriceps femoris muscle. The model was tested both with and without inertial loads placed around the ankle joints of healthy subjects. Results showed that the model predicted the knee extensions with a RMS angle error that was generally ⩽8°. The coefficients of determination between the measured and predicted data showed the model accounted for ∼71%, ∼94%, ∼73%, and ∼89% of the variances in the experimental maximum excursion, time to maximum excursion, maximum shortening velocity, and time to maximum shortening velocity, respectively. This study showed that our general non-isometric model predicted the lower limb motion in response to a range of stimulation frequencies and patterns, and external loads. This model can be implemented in an algorithm for controlling the position of the lower leg during the swing phase of gait during functional electrical stimulation.