EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis
Identifieur interne : 000941 ( Main/Exploration ); précédent : 000940; suivant : 000942EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis
Auteurs : Strahinja Dosen [Allemagne] ; Marko Markovic [Allemagne] ; Kelef Somer [Allemagne] ; Bernhard Graimann [Allemagne] ; Dario Farina [Allemagne]Source :
- Journal of NeuroEngineering and Rehabilitation [ 1743-0003 ] ; 2015.
Abstract
Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback).
As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task.
During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees.
The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively (routine grasping) and with a finer resolution (force steering). The future step will be to implement this promising and simple approach using an electrotactile interface. A prosthesis with a reliable response, following faithfully user intentions, would improve the utility during daily-life use and also facilitate the embodiment of the assistive system.
The online version of this article (doi:10.1186/s12984-015-0047-z) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s12984-015-0047-z
PubMed: 26088323
PubMed Central: 4485858
Affiliations:
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type="city">Göttingen</settlement></placeName></affiliation></author><author><name sortKey="Graimann, Bernhard" sort="Graimann, Bernhard" uniqKey="Graimann B" first="Bernhard" last="Graimann">Bernhard Graimann</name><affiliation wicri:level="1"><nlm:aff id="Aff2">Otto Bock HealthCare GmbH, 37115 Duderstadt, Germany</nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea>Otto Bock HealthCare GmbH, 37115 Duderstadt</wicri:regionArea><wicri:noRegion>37115 Duderstadt</wicri:noRegion><wicri:noRegion>37115 Duderstadt</wicri:noRegion><wicri:noRegion>37115 Duderstadt</wicri:noRegion></affiliation></author><author><name sortKey="Farina, Dario" sort="Farina, Dario" uniqKey="Farina D" first="Dario" last="Farina">Dario Farina</name><affiliation wicri:level="3"><nlm:aff id="Aff1">Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, 37075 Göttingen, Germany</nlm:aff><country 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type="wicri:Area/Main/Merge">000941</idno><idno type="wicri:Area/Main/Curation">000941</idno><idno type="wicri:Area/Main/Exploration">000941</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis</title><author><name sortKey="Dosen, Strahinja" sort="Dosen, Strahinja" uniqKey="Dosen S" first="Strahinja" last="Dosen">Strahinja Dosen</name><affiliation wicri:level="3"><nlm:aff id="Aff1">Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, 37075 Göttingen, Germany</nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea>Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, 37075 Göttingen</wicri:regionArea><placeName><region type="land" nuts="2">Basse-Saxe</region><settlement type="city">Göttingen</settlement></placeName></affiliation></author><author><name sortKey="Markovic, Marko" sort="Markovic, Marko" uniqKey="Markovic M" first="Marko" last="Markovic">Marko Markovic</name><affiliation wicri:level="1"><nlm:aff id="Aff2">Otto Bock HealthCare GmbH, 37115 Duderstadt, Germany</nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea>Otto Bock HealthCare GmbH, 37115 Duderstadt</wicri:regionArea><wicri:noRegion>37115 Duderstadt</wicri:noRegion><wicri:noRegion>37115 Duderstadt</wicri:noRegion><wicri:noRegion>37115 Duderstadt</wicri:noRegion></affiliation></author><author><name sortKey="Somer, Kelef" sort="Somer, Kelef" uniqKey="Somer K" first="Kelef" last="Somer">Kelef Somer</name><affiliation wicri:level="3"><nlm:aff id="Aff1">Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, 37075 Göttingen, Germany</nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea>Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, 37075 Göttingen</wicri:regionArea><placeName><region type="land" nuts="2">Basse-Saxe</region><settlement type="city">Göttingen</settlement></placeName></affiliation></author><author><name sortKey="Graimann, Bernhard" sort="Graimann, Bernhard" uniqKey="Graimann B" first="Bernhard" last="Graimann">Bernhard Graimann</name><affiliation wicri:level="1"><nlm:aff id="Aff2">Otto Bock HealthCare GmbH, 37115 Duderstadt, Germany</nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea>Otto Bock HealthCare GmbH, 37115 Duderstadt</wicri:regionArea><wicri:noRegion>37115 Duderstadt</wicri:noRegion><wicri:noRegion>37115 Duderstadt</wicri:noRegion><wicri:noRegion>37115 Duderstadt</wicri:noRegion></affiliation></author><author><name sortKey="Farina, Dario" sort="Farina, Dario" uniqKey="Farina D" first="Dario" last="Farina">Dario Farina</name><affiliation wicri:level="3"><nlm:aff id="Aff1">Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, 37075 Göttingen, Germany</nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea>Department of Neurorehabilitation Engineering, University Medical Center Göttingen (UMG), Georg-August University, 37075 Göttingen</wicri:regionArea><placeName><region type="land" nuts="2">Basse-Saxe</region><settlement type="city">Göttingen</settlement></placeName></affiliation></author></analytic><series><title level="j">Journal of NeuroEngineering and Rehabilitation</title><idno type="eISSN">1743-0003</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback).</p></sec><sec><title>Methods</title><p>As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task.</p></sec><sec><title>Results</title><p>During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees.</p></sec><sec><title>Conclusions</title><p>The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively (routine grasping) and with a finer resolution (force steering). The future step will be to implement this promising and simple approach using an electrotactile interface. A prosthesis with a reliable response, following faithfully user intentions, would improve the utility during daily-life use and also facilitate the embodiment of the assistive system.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/s12984-015-0047-z) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Mackenzie, C" uniqKey="Mackenzie C">C MacKenzie</name></author><author><name sortKey="Iberall, T" uniqKey="Iberall T">T Iberall</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Parker, P" uniqKey="Parker P">P Parker</name></author><author><name sortKey="Englehart, K" uniqKey="Englehart K">K Englehart</name></author><author><name sortKey="Hudgins, B" uniqKey="Hudgins B">B Hudgins</name></author></analytic></biblStruct><biblStruct><analytic><author><name 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