Imperial College London
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ProfessorDarioFarina

Faculty of Engineering, Department of Bioengineering

Chair in Neurorehabilitation Engineering
 
 
 
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Contact

 

+44 (0)20 7594 1387d.farina Website

 
 
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Location

 

RSM 4.15Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Mouchoux:2021:10.1109/tro.2020.3047013,
author = {Mouchoux, J and Carisi, S and Dosen, S and Farina, D and Schilling, AF and Markovic, M},
doi = {10.1109/tro.2020.3047013},
journal = {IEEE Transactions on Robotics},
pages = {1298--1312},
title = {Artificial perception and semiautonomous control in myoelectric hand prostheses increases performance and decreases effort},
url = {http://dx.doi.org/10.1109/tro.2020.3047013},
volume = {37},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Dexterous control of upper limb prostheses with multiarticulated wrists/hands is still a challenge due to the limitations of myoelectric man–machine interfaces. Multiple factors limit the overall performance and usability of these interfaces, such as the need to control degrees of freedom sequentially and not concurrently, and the inaccuracies in decoding the user intent from weak or fatigued muscles. In this article, we developed a novel man–machine interface that endows a myoelectric prosthesis (MYO) with artificial perception, estimation of user intention, and intelligent control (MYO–PACE) to continuously support the user with automation while preparing the prosthesis for grasping. We compared the MYO–PACE against state-of-the-art myoelectric control (pattern recognition) in laboratory and clinical tests. For this purpose, eight able-bodied and two amputee individuals performed a standard clinical test consisting of a series of manipulation tasks (portion of the SHAP test), as well as a more complex sequence of transfer tasks in a cluttered scene. In all tests, the subjects not only completed the trials faster using the MYO–PACE but also achieved more efficient myoelectric control. These results demonstrate that the implementation of advanced perception, context interpretation, and autonomous decision-making into active prostheses improves control dexterity. Moreover, it also effectively supports the user by speeding up the preshaping phase of the movement and decreasing muscle use.
AU  - Mouchoux,J
AU  - Carisi,S
AU  - Dosen,S
AU  - Farina,D
AU  - Schilling,AF
AU  - Markovic,M
DO  - 10.1109/tro.2020.3047013
EP  - 1312
PY  - 2021///
SN  - 1552-3098
SP  - 1298
TI  - Artificial perception and semiautonomous control in myoelectric hand prostheses increases performance and decreases effort
T2  - IEEE Transactions on Robotics
UR  - http://dx.doi.org/10.1109/tro.2020.3047013
UR  - https://ieeexplore.ieee.org/document/9366311
UR  - http://hdl.handle.net/10044/1/89754
VL  - 37
ER  -
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