A Comprehensive Framework for the Modelling of Cartesian Force Output in Human Limbs

Abstract

Neuromuscular functional electrical stimulation represents a valid technique for functional rehabilitation or, in the form of a neuroprosthesis, for the assistance of neurological patients. However, the selected stimulation of single muscles through surface electrodes remains challenging particularly for the upper extremity. In this paper, we present the MyoCeption, a comprehensive setup, which enables intuitive modeling of the user's musculoskeletal system, as well as proportional stimulation of the muscles with 16-bit resolution through up to 10 channels. The system can be used to provide open-loop force control, which, if coupled with an adequate body tracking system, can be used to implement an impedance control where the control loop is closed around the body posture. The system is completely self-contained and can be used in a wide array of scenarios, from rehabilitation to VR to teleoperation. Here, the MyoCeption's control environment has been experimentally validated through comparison with a third-party simulation suite. The results indicate that the musculoskeletal model used for the MyoCeption provides muscle geometries that are qualitatively similar to those computed in the baseline model.

Omnidirectional endpoint force control through functional electrical stimulation

“…While the purpose of condition 4 is to verify whether any benefit deriving from the FES device's calibration are due to the geometrical adjustments of the musculoskeletal model or due to the adjustment to stimulation intensity, the expected outcome in the latter case would have been a better performance than using the non-calibrated FES device, but worse than the fully calibrated condition. The fact that the correlation is worse than both C2 and C3 would seem to indicate that the most likely cause of this decrease in performance is fatigue and other progressive effects, which are well documented in FES applications [26,27]. In this regard, the study design could have benefited from randomizing the order of conditions C2-C4, or at the very least from allowing more resting time between trials.…”

“…Looking at possible implementations using such a regression machine in order to control a FES setup, the results reported in the works by Schearer et al [12] and Friedrich et al [28] can be helpful, mainly because of their finding that muscle stimulation can be modelled as combining linearly in the force output space. As demonstrated in [27], this fact can be employed to design ridge regression-based FES controllers which can facilitate movement with a time-effective calibration procedure, once the electrodes are in place. The work by Schearer et al, in particular, presents an experiment which employs a setup in many ways identical to that adopted in the present study.…”

“…On the one hand, black box approaches typically have to sample the effects of muscle contractions in various postures [7,8]. Musculoskeletal models, on the other hand, can inherently account for at least some effects of posture changes [9,10]. In robotics, impedance-based controls can be used to impose a certain dynamic behaviour between a robot and its environment [11].…”

“…While this device proposes to be a general-purpose platform designed to test various control algorithms, here the system is driven by a musculoskeletal model presented and validated in [9]. Therein, the musculoskeletal model was tested against a third-party model introduced in [10], which was taken as baseline.…”