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Key insights into hand biomechanics: Human grip stiffness can be decoupled from force by cocontraction and predicted from electromyography

Höppner, Hannes und Stillfried, Georg und Große-Dunker, Maximilian und Bayer, Justin und van der Smagt, Patrick (2016) Key insights into hand biomechanics: Human grip stiffness can be decoupled from force by cocontraction and predicted from electromyography. Frontiers in Neurorobotics, 11. Frontiers Media S.A.. doi: 10.3389/fnbot.2017.00017. ISSN 1662-5218.

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Offizielle URL: http://journal.frontiersin.org/article/10.3389/fnbot.2017.00017/

Kurzfassung

We investigate the relation between grip force and grip stiffness for the human hand with and without voluntary cocontraction. Apart from gaining biomechanical insight, this issue is particularly relevant for variable-stiffness robotic systems, which can independently control the two parameters, but for which no clear methods exist to design or efficiently exploit them. Subjects were asked in one task to produce different levels of force, and stiffness was measured. As expected, this task reveals a linear coupling between force and stiffness. In a second task, subjects were then asked to additionally decouple stiffness from force at these force levels by using cocontraction. We measured the electromyogram from relevant groups of muscles and analyzed the possibility to predict stiffness and force. Optical tracking was used for avoiding wrist movements. We found that subjects were able to decouple grip stiffness from force when using cocontraction on average by about 20% of the maximum measured stiffness over all force levels, while this ability increased with the applied force. This result contradicts the force–stiffness behavior of most variable-stiffness actuators. Moreover, we found the thumb to be on average twice as stiff as the index finger and discovered that intrinsic hand muscles predominate our prediction of stiffness, but not of force. EMG activity and grip force allowed to explain 72 ± 12% of the measured variance in stiffness by simple linear regression, while only 33 ± 18% variance in force. Conclusively the high signal-to-noise ratio and the high correlation to stiffness of these muscles allow for a robust and reliable regression of stiffness, which can be used to continuously teleoperate compliance of modern robotic hands.

elib-URL des Eintrags:https://elib.dlr.de/110122/
Dokumentart:Zeitschriftenbeitrag
Titel:Key insights into hand biomechanics: Human grip stiffness can be decoupled from force by cocontraction and predicted from electromyography
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Höppner, HannesHannes.Hoeppner (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Stillfried, GeorgGeorg.Stillfried (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Große-Dunker, Maximilianmaximilian (at) grosse-dunker.euNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Bayer, Justinbayer.justin (at) googlemail.comNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
van der Smagt, Patricksmagt (at) brml.orgNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:21 Dezember 2016
Erschienen in:Frontiers in Neurorobotics
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:11
DOI:10.3389/fnbot.2017.00017
Verlag:Frontiers Media S.A.
ISSN:1662-5218
Status:veröffentlicht
Stichwörter:Grip Stiffness, grip force, intrinsic hand muscles, Interosseus muscles, Electromyography, Co-contraction, soft robotics, Variable-Stiffness Actuators, Robotic hand-design
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Technik für Raumfahrtsysteme
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R SY - Technik für Raumfahrtsysteme
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben Weiterentwicklung Robotik - Mechatronik und Dynamik (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Robotik und Mechatronik (ab 2013) > Mechatronische Komponenten und Systeme
Institut für Robotik und Mechatronik (ab 2013) > Kognitive Robotik
Hinterlegt von: Höppner, Hannes
Hinterlegt am:04 Jan 2017 10:35
Letzte Änderung:27 Nov 2023 14:07

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