RT Journal Article
T1 A High-Level Control Algorithm Based on sEMG Signalling for an Elbow Joint SMA Exoskeleton
A1 Copaci, Dorin Sabin
A1 Serrano del Cerro, David
A1 Moreno Lorente, Luis Enrique
A1 Blanco Rojas, María Dolores
AB 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.
PB MDPI
SN 1424-8220
YR 2018
FD 2018-08-02
LK https://hdl.handle.net/10016/28027
UL https://hdl.handle.net/10016/28027
LA eng
NO The research was funded by RoboHealth (DPI2013-47944-C4-3-R) and the EDAM (DPI2016-75346-R) Spanish research projects.
DS e-Archivo
RD 1 sept. 2024