Electromyography based joint angle estimation and control of a robotic leg

Abstract

Musculoskeletal modeling based on Electromyography (EMG) has many applications in physiotherapy and biologically-inspired robotics. In this article, a novel methodology for the modeling of the dynamics of an antagonistic muscle pair that actuates the human ankle joint movements will be established. As it will be presented, the musculoskeletal model is based on a multi input single output (MISO) auto-regressive integrated moving average with exogenous input (ARIMAX) model, which takes the integrated EMG measurements as input and estimates the corresponding joint angles. Based on this methodology, a Pneumatic Artificial Muscle (PAM) robotic leg setup that mimics the flexion/extension movement of human ankle joint is controlled to replicate the human movement. The experimental results demonstrate the performance of EMG-based joint angle estimation and control of the robotic leg with the proposed model.