A myosignal-based powered exoskeleton system
Abstract
This paper studies the integration of a human arm with a powered exoskeleton (orthotic device) and its experimental implementation in an elbow joint, naturally controlled by the human. The human-machine interface was set at the neuromuscular level, by using the neuromuscular signal (EMG) as the primary command signal for the exoskeleton system. The EMG signal along with the joint kinematics were fed into a myoprocessor which in turn predicted the muscle moments on the elbow joint. The moment-based control system integrated myoprocessor moment prediction with feedback moments measured at the human arm/exoskeleton and external load/exoskeleton interfaces. The exoskeleton structure under study was a two-link, two-joint mechanism, corresponding to the arm limbs and joints, which was mechanically linked by the human operator. Four indices of performance were used to define the quality of the human/machine integration and to evaluate the operational envelope of the system. Experimental results indicate the feasibility of an EMG-based power exoskeleton system as an integrated human-machine system using high-level neurological signals.
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Using this myoprocessor scheme, a one-degree-of-freedom exoskeleton was controlled using dynamic, kinematic, and physiological feedback.
“Using this schemea one-degree-of-freedom exoskeleton has been controlled using a multiple-feedback approach: (1) dynamic feedback - the moments generated at the interfaces between the human arm, the external load, and the exoskeleton structure; (2) kinematic feedback -the joint angular trajectories recorded using encoders, and the angular velocity and acceleration calculated by finite differences;”
From A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems (2005) · cites this paper as Rosen et al., 2001
Experimental tests have shown that use of sEMG significantly improved the mechanical gain of the system while maintaining natural control.
“Experimental tests have shown that the use of sEMG significantly improved the mechanical gain of the system (i.e., the possibility of augmenting capabilities and/or reducing human muscular efforts to carry out the different tasks) while maintaining natural control of the system.”
From A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems (2005) · cites this paper as Rosen et al., 2001
Rosen et al. developed a myoprocessor based on the Hill model of muscular activation to extract force/torque information from muscle information.
“Rosen et al. (2001) developed a 'myoprocessor' based on the Hill model of muscular activation to extract force/torque information from muscle information.”
From A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems (2005) · cites this paper as Rosen et al., 2001
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References 45 · Cited by 437
- Authors
- Rosen, J., Brand, M., Fuchs, M. B., & Arcan, M.
- Affiliations
- Tel Aviv University (IL)
- ORCID
- Brand, M.
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans
- Published
- 2001-05
- Volume
- 31
- Issue
- 3
- Pages
- 210-222
- ISSN
- 1083-4427 (ISSN-L)
- OpenAlex
- W2168117107
- Cited by
- 437
- References
- 45
- Citations by year
- 2026: 3 · 2025: 13 · 2024: 13 · 2023: 14 · 2022: 18 · 2021: 18 · 2020: 21 · 2019: 29 · 2018: 24 · 2017: 30 · 2016: 29 · 2015: 16 · 2014: 21 · 2013: 25 · 2012: 18
- FWCI
- 4.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- powered exoskeleton, electromyography, elbow, human-machine interaction, neuromuscular control, orthoses, human-machine integration
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