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Erschienen in: Artificial Life and Robotics 2/2019

23.11.2018 | Original Article

An exoskeletal motion instruction with active/passive hybrid movement: effect of stiffness of haptic-device force-feedback system

verfasst von: Fumihiro Akatsuka, Yoshihiko Nomura, Tokuhiro Sugiura, Takaaki Yasui

Erschienen in: Artificial Life and Robotics | Ausgabe 2/2019

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Abstract

Haptic devices have been studied as a useful tool for motion instruction. In this paper, we take up the method in which the device momentarily instructs the learners to reduce errors of their reproduced movements by giving force. Subjects trained two-stroke hand motions on a horizontal plane. The subjects learned lengths, angles, and velocities of each of the two strokes. The device-exerted force was calculated by multiplying a stiffness to the momentary joint angular errors. The servomotor stiffness with respect to a geared-motor rotation was chosen from 0.5, 1.5, 4.5, 13.5, and 40.5 N cm/deg. The experiment constituted of the training stage and the short-term recall stage. In the instruction trials, subjects were asked to “actively” conduct their recognized movement and to modify their momentary movements, perceiving the device-forced passive movement and/or device-exerted force. The experimental results showed that the reproduction errors in the short-term recall stage under the larger stiffness conditions were approximately smaller. However, the error reduction of the length tended to converge for 4.5 N cm/deg or more condition, and the error reductions of the angle and average velocity tended to converge for 13.5 N cm/deg or more condition. In addition, maximum device forces given in the instruction trials tended to increase as the stiffness increased.

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Metadaten
Titel
An exoskeletal motion instruction with active/passive hybrid movement: effect of stiffness of haptic-device force-feedback system
verfasst von
Fumihiro Akatsuka
Yoshihiko Nomura
Tokuhiro Sugiura
Takaaki Yasui
Publikationsdatum
23.11.2018
Verlag
Springer Japan
Erschienen in
Artificial Life and Robotics / Ausgabe 2/2019
Print ISSN: 1433-5298
Elektronische ISSN: 1614-7456
DOI
https://doi.org/10.1007/s10015-018-0504-4

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