Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand.
Adaptive synergies
Bionic hand
Myoelectric control
Soft robotics
Journal
Journal of neuroengineering and rehabilitation
ISSN: 1743-0003
Titre abrégé: J Neuroeng Rehabil
Pays: England
ID NLM: 101232233
Informations de publication
Date de publication:
25 08 2020
25 08 2020
Historique:
received:
30
12
2019
accepted:
04
08
2020
entrez:
27
8
2020
pubmed:
28
8
2020
medline:
15
12
2020
Statut:
epublish
Résumé
State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently, the translation of neuroscientific theories (i.e. postural synergies) in software and hardware architecture of artificial devices is opening new approaches for the design and control of upper-limb prostheses. Following these emerging principles, previous research on the SoftHand Pro, which embeds one physical synergy, showed promising results in terms of intuitiveness, robustness, and grasping performance. To explore these principles also in hands with augmented capabilities, this paper describes the SoftHand 2 Pro, a second generation of the device with 19 degrees-of-freedom and a second synergistic layer. After a description of the proposed device, the work explores a continuous switching control method based on a myoelectric pattern recognition classifier. The combined system was validated using standardized assessments with able-bodied and, for the first time, amputee subjects. Results show an average improvement of more than 30% of fine grasp capabilities and about 10% of hand function compared with the first generation SoftHand Pro. Encouraging results suggest how this approach could be a viable way towards the design of more natural, reliable, and intuitive dexterous hands.
Sections du résumé
BACKGROUND
State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently, the translation of neuroscientific theories (i.e. postural synergies) in software and hardware architecture of artificial devices is opening new approaches for the design and control of upper-limb prostheses.
METHODS
Following these emerging principles, previous research on the SoftHand Pro, which embeds one physical synergy, showed promising results in terms of intuitiveness, robustness, and grasping performance. To explore these principles also in hands with augmented capabilities, this paper describes the SoftHand 2 Pro, a second generation of the device with 19 degrees-of-freedom and a second synergistic layer. After a description of the proposed device, the work explores a continuous switching control method based on a myoelectric pattern recognition classifier.
RESULTS
The combined system was validated using standardized assessments with able-bodied and, for the first time, amputee subjects. Results show an average improvement of more than 30% of fine grasp capabilities and about 10% of hand function compared with the first generation SoftHand Pro.
CONCLUSIONS
Encouraging results suggest how this approach could be a viable way towards the design of more natural, reliable, and intuitive dexterous hands.
Identifiants
pubmed: 32843058
doi: 10.1186/s12984-020-00741-y
pii: 10.1186/s12984-020-00741-y
pmc: PMC7447577
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
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