Gaze, visual, myoelectric, and inertial data of grasps for intelligent prosthetics

Cognolato, Matteo (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland) ; Gijsberts, Arjan (Istituto Italiano di Tecnologia, Genoa, Italy) ; Gregori, Valentina (Istituto Italiano di Tecnologia, Genoa, Italy ; Department of Computer, Control, and Management Engineering, University of Rome La Sapienza, Rome, Italy) ; Saetta, Gianluca (Department of Neurology, University Hospital of Zurich, Zurich, Switzerland) ; Giacomino, Katia (Department of Physical Therapy, University of Applied Sciences Western Switzerland (HES-SO Valais), Leukerbad, Switzerland) ; Mittaz Hager, Anne-Gabrielle (Department of Physical Therapy, University of Applied Sciences Western Switzerland (HES-SO Valais), Leukerbad, Switzerland) ; Gigli, Andrea (Istituto Italiano di Tecnologia, Genoa, Italy) ; Faccio, Diego (Clinic of Plastic Surgery, Padova University Hospital, Padova, Italy) ; Tiengo, Cesare (Clinic of Plastic Surgery, Padova University Hospital, Padova, Italy) ; Bassetto, Franco (Clinic of Plastic Surgery, Padova University Hospital, Padova, Italy) ; Caputo, Barbara (Istituto Italiano di Tecnologia, Genoa, Italy ; Politecnico di Torino, Turin, Italy) ; Brugger, Peter (Department of Neurology, University Hospital of Zurich, Zurich, Switzerland ; Rehabilitation Center Valens, Valens, Switzerland) ; Atzori, Manfredo (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Müller, Henning (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; University of Geneva, Geneva, Switzerland)

A hand amputation is a highly disabling event, having severe physical and psychological repercussions on a person’s life. Despite extensive efforts devoted to restoring the missing functionality via dexterous myoelectric hand prostheses, natural and robust control usable in everyday life is still challenging. Novel techniques have been proposed to overcome the current limitations, among them the fusion of surface electromyography with other sources of contextual information. We present a dataset to investigate the inclusion of eye tracking and first person video to provide more stable intent recognition for prosthetic control. This multimodal dataset contains surface electromyography and accelerometry of the forearm, and gaze, first person video, and inertial measurements of the head recorded from 15 transradial amputees and 30 able-bodied subjects performing grasping tasks. Besides the intended application for upper-limb prosthetics, we also foresee uses for this dataset to study eye-hand coordination in the context of psychophysics, neuroscience, and assistive robotics.


Article Type:
scientifique
Faculty:
Economie et Services
Santé
School:
HEdS-VS
HEG-VS
Institute:
Institut Informatique de gestion
Institut Santé
Date:
2020-02
Pagination:
15 p.
Published in:
Scientific Data
Numeration (vol. no.):
2020, vol. 7, no 43, pp. 1-15
DOI:
ISSN:
2052-4463
Appears in Collection:



 Record created 2020-02-27, last modified 2020-03-25

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