Neuromuscular interfacing: A novel approach to EMG-driven multiple DOF physiological models

Abstract

This paper presents a novel approach that involves first identifying and verifying the available superficial muscles that can be recorded by surface electromyography (EMG) signals, and then developing a musculoskeletal model based on these findings, which have specifically independent DOFs for movement. Such independently controlled multiple DOF EMG-driven models have not been previously developed and a two DOF model for the masticatory system was achieved by implementing independent antagonist muscle combinations for vertical and lateral movements of the jaw. The model has six channels of EMG signals from the bilateral temporalis, masseter and digastric muscles to predict the motion of the mandible. This can be used in a neuromuscular interface to manipulate a jaw exoskeleton for rehabilitation. For a range of different complexities of jaw movements, the presented model is able to consistently identify movements with 0.28 - 0.46 average normalized RMSE. The results demonstrate the feasibility of the approach at determining complex multiple DOF movements and its applicability to any joint system.

A hybrid BMI-based exoskeleton for paresis: EMG control for assisting arm movements

“…Additionally, our method introduced a multi-joint musculoskeletal model for the MP joint and wrist, including biarticular muscles, and successfully suppressed the errors during marked wrist flexion or extension. Although some researchers have developed methods to estimate an elbow joint angle (Pau et al 2012) and motion of a jaw (Pau et al 2013) using musculoskeletal models, their methods have not been applied to multi-joint movements with biarticular muscle interaction.…”