Electromyography data for non-invasive naturally-controlled robotic hand prostheses

Manfredo Atzori; Arjan Gijsberts; Claudio Castellini; Barbara Caputo; Anne-Gabrielle Mittaz Hager; Simone Elsig; Giorgio Giatsidis; Franco Bassetto; Henning Müller

doi:10.1038/sdata.2014.53

journal article Open Access Dec 23, 2014

Electromyography data for non-invasive naturally-controlled robotic hand prostheses

Manfredo Atzori

Arjan Gijsberts Claudio Castellini

Barbara Caputo Anne-Gabrielle Mittaz Hager Simone Elsig Giorgio Giatsidis Franco Bassetto Henning Müller

Scientific Data Vol. 1 No. 1 · Springer Science and Business Media LLC

View at Publisher Save 10.1038/sdata.2014.53

Abstract

AbstractRecent advances in rehabilitation robotics suggest that it may be possible for hand-amputated subjects to recover at least a significant part of the lost hand functionality. The control of robotic prosthetic hands using non-invasive techniques is still a challenge in real life: myoelectric prostheses give limited control capabilities, the control is often unnatural and must be learned through long training times. Meanwhile, scientific literature results are promising but they are still far from fulfilling real-life needs. This work aims to close this gap by allowing worldwide research groups to develop and test movement recognition and force control algorithms on a benchmark scientific database. The database is targeted at studying the relationship between surface electromyography, hand kinematics and hand forces, with the final goal of developing non-invasive, naturally controlled, robotic hand prostheses. The validation section verifies that the data are similar to data acquired in real-life conditions, and that recognition of different hand tasks by applying state-of-the-art signal features and machine-learning algorithms is possible.

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Details

Published: Dec 23, 2014
Vol/Issue: 1(1)
License: View

Authors

M

Manfredo Atzori

Information Systems Institute, University of Applied Sciences Western Switzerland (HES-SO Valais), Sierre, Switzerland

Anne-Gabrielle Mittaz Hager

Cite This Article

Manfredo Atzori, Arjan Gijsberts, Claudio Castellini, et al. (2014). Electromyography data for non-invasive naturally-controlled robotic hand prostheses. Scientific Data, 1(1). https://doi.org/10.1038/sdata.2014.53

Electromyography data for non-invasive naturally-controlled robotic hand prostheses

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