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Open AccessArticle

A High-Level Control Algorithm Based on sEMG Signalling for an Elbow Joint SMA Exoskeleton

Department of Systems Engineering and Automation, Carlos III University of Madrid, 28911 Leganés, Madrid, Spain
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2018, 18(8), 2522;
Received: 19 June 2018 / Revised: 22 July 2018 / Accepted: 30 July 2018 / Published: 2 August 2018
(This article belongs to the Special Issue Assistance Robotics and Biosensors)
A high-level control algorithm capable of generating position and torque references from surface electromyography signals (sEMG) was designed. It was applied to a shape memory alloy (SMA)-actuated exoskeleton used in active rehabilitation therapies for elbow joints. The sEMG signals are filtered and normalized according to data collected online during the first seconds of a therapy session. The control algorithm uses the sEMG signals to promote active participation of patients during the therapy session. In order to generate the reference position pattern with good precision, the sEMG normalized signal is compared with a pressure sensor signal to detect the intention of each movement. The algorithm was tested in simulations and with healthy people for control of an elbow exoskeleton in flexion–extension movements. The results indicate that sEMG signals from elbow muscles, in combination with pressure sensors that measure arm–exoskeleton interaction, can be used as inputs for the control algorithm, which adapts the reference for exoskeleton movements according to a patient’s intention. View Full-Text
Keywords: exoskeleton; electromyographic (EMG); control systems exoskeleton; electromyographic (EMG); control systems
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MDPI and ACS Style

Copaci, D.; Serrano, D.; Moreno, L.; Blanco, D. A High-Level Control Algorithm Based on sEMG Signalling for an Elbow Joint SMA Exoskeleton. Sensors 2018, 18, 2522.

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