Voluntary Control of an Ankle Joint Exoskeleton by Able-Bodied Individuals and Stroke Survivors Using EMG-Based Admittance Control Scheme.

Zhuang, Y; Leng, Y; Zhou, J; Song, R; Li, L; Su, SW

Voluntary Control of an Ankle Joint Exoskeleton by Able-Bodied Individuals and Stroke Survivors Using EMG-Based Admittance Control Scheme.

Zhuang, Y Leng, Y Zhou, J Song, R Li, L Su, SW

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Trans Biomed Eng, 2021, 68, (2), pp. 695-705
Issue Date:: 2021-02

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Field	Value	Language
dc.contributor.author	Zhuang, Y
dc.contributor.author	Leng, Y
dc.contributor.author	Zhou, J
dc.contributor.author	Song, R
dc.contributor.author	Li, L
dc.contributor.author	Su, SW
dc.date.accessioned	2022-05-23T01:05:06Z
dc.date.available	2022-05-23T01:05:06Z
dc.date.issued	2021-02
dc.identifier.citation	IEEE Trans Biomed Eng, 2021, 68, (2), pp. 695-705
dc.identifier.issn	0018-9294
dc.identifier.issn	1558-2531
dc.identifier.uri	http://hdl.handle.net/10453/157613
dc.description.abstract	Control schemes based on electromyography (EMG) have demonstrated their superiority in human-robot cooperation due to the fact that motion intention can be well estimated by EMG signals. However, there are several limitations due to the noisy nature of EMG signals and the inaccuracy of EMG-force/torque estimation, which might deteriorate the stability of human-robot cooperation movement. To improve the movement stability, an EMG-based admittance control scheme (EACS) was proposed, comprised of an EMG-driven musculoskeletal model (EDMM), an admittance filter and an inner position controller. To investigate the performance of EACS, a series of sinusoidal tracking tasks were conducted with 12 healthy participants and 4 stroke survivors in an ankle exoskeleton in comparison with the EMG-based open-loop control scheme (EOCS). The experimental results indicated that both EACS and EOCS could improve stroke survivors' ankle range of motion (ROM). The experimental results of both healthy participants and stroke survivors showed that the assistance torque, tracking error and jerk values of EACS were lower than those of EOCS. The interaction torque of EACS decreased towards the increasing assistance ratio while that of EOCS increased. Moreover, the EMG levels of tibialis anterior (TA) decreased towards the increasing assistance ratio but were higher than those of EOCS. EACS was effective in improving movements stability, and had the potential to be applied in robot-assisted rehabilitation training to address the foot-drop problem.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Trans Biomed Eng
dc.relation.isbasedon	10.1109/TBME.2020.3012296
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0903 Biomedical Engineering, 0906 Electrical and Electronic Engineering
dc.subject.classification	Biomedical Engineering
dc.subject.mesh	Ankle Joint
dc.subject.mesh	Electromyography
dc.subject.mesh	Exoskeleton Device
dc.subject.mesh	Humans
dc.subject.mesh	Stroke
dc.subject.mesh	Stroke Rehabilitation
dc.subject.mesh	Survivors
dc.subject.mesh	Ankle Joint
dc.subject.mesh	Humans
dc.subject.mesh	Electromyography
dc.subject.mesh	Survivors
dc.subject.mesh	Stroke
dc.subject.mesh	Exoskeleton Device
dc.subject.mesh	Stroke Rehabilitation
dc.title	Voluntary Control of an Ankle Joint Exoskeleton by Able-Bodied Individuals and Stroke Survivors Using EMG-Based Admittance Control Scheme.
dc.type	Journal Article
utslib.citation.volume	68
utslib.location.activity	United States
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0903 Biomedical Engineering
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Centre for Health Technologies (CHT)
utslib.copyright.status	closed_access	*
dc.date.updated	2022-05-23T01:05:00Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	68
utslib.citation.issue	2

Abstract:

Control schemes based on electromyography (EMG) have demonstrated their superiority in human-robot cooperation due to the fact that motion intention can be well estimated by EMG signals. However, there are several limitations due to the noisy nature of EMG signals and the inaccuracy of EMG-force/torque estimation, which might deteriorate the stability of human-robot cooperation movement. To improve the movement stability, an EMG-based admittance control scheme (EACS) was proposed, comprised of an EMG-driven musculoskeletal model (EDMM), an admittance filter and an inner position controller. To investigate the performance of EACS, a series of sinusoidal tracking tasks were conducted with 12 healthy participants and 4 stroke survivors in an ankle exoskeleton in comparison with the EMG-based open-loop control scheme (EOCS). The experimental results indicated that both EACS and EOCS could improve stroke survivors' ankle range of motion (ROM). The experimental results of both healthy participants and stroke survivors showed that the assistance torque, tracking error and jerk values of EACS were lower than those of EOCS. The interaction torque of EACS decreased towards the increasing assistance ratio while that of EOCS increased. Moreover, the EMG levels of tibialis anterior (TA) decreased towards the increasing assistance ratio but were higher than those of EOCS. EACS was effective in improving movements stability, and had the potential to be applied in robot-assisted rehabilitation training to address the foot-drop problem.

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http://hdl.handle.net/10453/157613