Simulation of FES on the forearm with muscle-specific activation resolution - Baier, Johanna; Selkmann, Sascha; Bender, Beate (Frontiers in Bioengineering and Biotechnology, 2024)
Introduction Functional electrical stimulation (FES) is an established method to support neurological rehabilitation. But particularly at the forearm, it still lacks in the stimulation of selective muscle activations, that form the basis of complex hand movements. Current research approaches in the context of selective muscle activation often attempt to enable targeted stimulation by increasing the number of electrodes and combine them in electrode arrays. In order to determine the best stimulation positions and settings manual or semi-automated algorithms were used. This approach is limited due to experimental limitations. The supportive use of simulation studies is well established, but existing simulation models are not suitable for analyses with the aim of selective muscle activation due to missing or arbitrarily arranged innervation areas. Methods This study introduces a new modeling method to design a person-specific digital twin that enables the prediction of muscle activation during FES at the forearm. The designed individual model consists of three parts: an anatomically-based 3D volume conductor, a muscle-specific nerve fiber arrangement in various Regions of Interest (ROIs) and a standard nerve model. All processes were embedded in scripts or macros to enable automated changes of the model as well as the simulation setup. Results The experimental evaluation of simulated strength-duration diagrams showed a good coincidence. The relative differences of the simulated amplitudes to the mean amplitude of the four experiments were in the same range as the inter-experimental differences with mean values between 0.005 and 0.045. Based on this results muscle-specific activation thresholds were determined and integrated to the simulation process. With this modification simulated force-intensity curves showed a good agreement with additionally measured ones. Discussion The results show that the model is suitable to simulate realistic muscle-specific activations. Physiological complex hand movements are composed of individual, selective muscle activations, it can be assumed that the model is also suitable for simulating these. The presented approach therefore represents a new and very promising approach for the development of new applications and products in the context of the rehabilitation of sensorimotor disorders.