A quantitative taxonomy of human hand grasps

Stival, Francesca (Intelligent Autonomous Systems Lab (IAS-Lab), Department of Information Engineering (DEI), University of Padova, Padova, Italy; University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Michieletto, Stefano (Intelligent Autonomous Systems Lab (IAS-Lab), Department of Information Engineering (DEI), University of Padova, Padova, Italy) ; 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) ; Pagello, Enrico (Intelligent Autonomous Systems Lab (IAS-Lab), Department of Information Engineering (DEI), University of Padova, Padova, Italy;) ; Müller, Henning (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis); University of Geneva, Geneva, Switzerland) ; Atzori, Manfredo (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))

A proper modeling of human grasping and of hand movements is fundamental for robotics, prosthetics, physiology and rehabilitation. The taxonomies of hand grasps that have been proposed in scientific literature so far are based on qualitative analyses of the movements and thus they are usually not quantitatively justified. Methods This paper presents to the best of our knowledge the first quantitative taxonomy of hand grasps based on biomedical data measurements. The taxonomy is based on electromyography and kinematic data recorded from 40 healthy subjects performing 20 unique hand grasps. For each subject, a set of hierarchical trees are computed for several signal features. Afterwards, the trees are combined, first into modality-specific (i.e. muscular and kinematic) taxonomies of hand grasps and then into a general quantitative taxonomy of hand movements. The modality-specific taxonomies provide similar results despite describing different parameters of hand movements, one being muscular and the other kinematic. Results The general taxonomy merges the kinematic and muscular description into a comprehensive hierarchical structure. The obtained results clarify what has been proposed in the literature so far and they partially confirm the qualitative parameters used to create previous taxonomies of hand grasps. According to the results, hand movements can be divided into five movement categories defined based on the overall grasp shape, finger positioning and muscular activation. Part of the results appears qualitatively in accordance with previous results describing kinematic hand grasping synergies. Conclusions The taxonomy of hand grasps proposed in this paper clarifies with quantitative measurements what has been proposed in the field on a qualitative basis, thus having a potential impact on several scientific fields.


Keywords:
Article Type:
scientifique
Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Date:
2019-02
Pagination:
17 p.
Published in:
Journal of neuroengineering and rehabilitation
Numeration (vol. no.):
2019, vol. 16, no. 28
DOI:
ISSN:
1743-0003
Appears in Collection:



 Record created 2019-06-14, last modified 2019-07-05

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