sEMG-Based Control of an Exoskeleton Robot Arm

This paper investigates the processing of surface electromyographic (sEMG) signals collected from the forearm of a human subject and, based on which, a control strategy is developed for an exoskeleton arm. In this study, we map the motion of elbow and wrist to the corresponding joints of an exoskeleton arm. Linear Discriminant Analysis (LDA) based classifiers are introduced as the indicator of the motion type of the joints, and then with the force of corresponding agonist muscles the control signal is produced. In the strategy, which is different from the conventional method, we assign one classifier for each joint, decomposing the motion of the two joints into independent parts, making the recognition of the forearm motion a combination of the results of different joints. In addition, training time is reduced and recognition of motion is simplified.

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