Title :
Toward a Unified Framework for EMG Signals Processing and Controlling an Exoskeleton
Author :
Durandau, Guillaume ; Suleiman, Wassim
Author_Institution :
Comput. Eng. Dept., Univ. de Sherbrooke, Sherbrooke, QC, Canada
Abstract :
In this paper, we present a control method of robotic system using electromyography (EMG) signals collected by surface EMG electrodes. The EMG signals are analyzed using a neuromusculoskeletal (NMS) model that represents at the same time the muscle and the skeleton of the body. It has the advantage of adding external forces to the model without changing the initial parameters which is particularly useful for the control of exoskeletons. The algorithm has been validated through experiments consisting of moving only the elbow joint freely or while handling a barbell having various sets of loads. The results of our algorithm are then compared to the motions obtained by a motion capture system during the same session. The comparison points out the efficiency of our algorithm for predicting and estimating the arm motion using only EMG signals.
Keywords :
electromyography; medical robotics; medical signal processing; motion control; patient rehabilitation; EMG signal processing; arm motion estimation; arm motion prediction; elbow joint; electromyography; exoskeleton control; motion capture system; neuromusculoskeletal model; robotic system; surface EMG electrodes; Computational modeling; Elbow; Electromyography; Force; Joints; Muscles; Optimization; EMG; Neuromuscloskeletal model; electromyogram; exoskeleton; modeling;
Conference_Titel :
Computer and Robot Vision (CRV), 2014 Canadian Conference on
Conference_Location :
Montreal, QC
Print_ISBN :
978-1-4799-4338-8
DOI :
10.1109/CRV.2014.46