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Using the Bioelectric Signals to Control of Wearable Orthosis of the Elbow Joint with Bi-Muscular Pneumatic Servo-Drive

Published online by Cambridge University Press:  09 July 2019

Ryszard Dindorf Open the ORCID record for Ryszard Dindorf [Opens in a new window]  and
Piotr Wos
Ryszard Dindorf*
Affiliation:
Faculty of Mechatronics and Machine Design, Department of Mechatronic Devices, Kielce University of Technology, Kielce, Poland. E-mail: wos@tu.kielce.pl
Piotr Wos
Affiliation:
Faculty of Mechatronics and Machine Design, Department of Mechatronic Devices, Kielce University of Technology, Kielce, Poland. E-mail: wos@tu.kielce.pl
*
*Corresponding author. E-mail: dindorf@tu.kielce.pl
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Summary

This study presents a new design of a wearable orthosis of elbow joint with a bimuscular pneumatic servo-drive (PSD) with control based on the recording of bioelectric signals (BESs). The authors analyzed the impact of the induced brain activity and the muscular tension within the head of the participant on the BESs that can be used to control the PSD of the elbow joint orthosis. To control the elbow joint orthosis, a distributed control system (DCS) was developed, which contains two control layers: a master layer connected to the device for recording the BES and a direct layer contained in a wireless manner with the controller of the PSD. A kinematic-dynamic model of the elbow joint orthosis, patterned after the biological model of human biceps–triceps, was used in the programming of the PSD controller. A biomimetic dynamic model of the pneumatic muscle actuator (PMA) was used, in which the contraction force results from the adopted exponential static model of the pneumatic muscle (PM). The use of direct visual feedback (DVF) makes it possible for the participant to focus on the movement of the orthosis taking into account the motoric functions of the elbow.

Keywords

Bimuscular driving systemPneumatic servo-driveWearable elbow orthosisWireless interface controllerBioelectric signals
Type
Articles
Information
Robotica , Volume 38 , Issue 5 , May 2020 , pp. 804 - 818
Copyright
Copyright © Cambridge University Press 2019

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