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research article

Toward higher-performance bionic limbs for wider clinical use

Farina, Dario
•
Vujaklija, Ivan
•
Branemark, Rickard
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2023
Nature Biomedical Engineering

Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by the user as belonging to their own body. Robotic limbs can convey information about the environment with higher precision than biological limbs, but their actual performance is substantially limited by current technologies for the interfacing of the robotic devices with the body and for transferring motor and sensory information bidirectionally between the prosthesis and the user. In this Perspective, we argue that direct skeletal attachment of bionic devices via osseointegration, the amplification of neural signals by targeted muscle innervation, improved prosthesis control via implanted muscle sensors and advanced algorithms, and the provision of sensory feedback by means of electrodes implanted in peripheral nerves, should all be leveraged towards the creation of a new generation of high-performance bionic limbs. These technologies have been clinically tested in humans, and alongside mechanical redesigns and adequate rehabilitation training should facilitate the wider clinical use of bionic limbs.

This Perspective argues that technologies for the neural interfacing of robotic devices with the body that have been clinically tested in humans should be leveraged toward the creation of a new generation of high-performance bionic limbs.

  • Details
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Type
research article
DOI
10.1038/s41551-021-00732-x
Web of Science ID

WOS:000656399300002

Author(s)
Farina, Dario
Vujaklija, Ivan
Branemark, Rickard
Bull, Anthony M. J.
Dietl, Hans
Graimann, Bernhard
Hargrove, Levi J.
Hoffmann, Klaus-Peter
Huang, He (Helen)
Ingvarsson, Thorvaldur
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Date Issued

2023

Publisher

NATURE RESEARCH

Published in
Nature Biomedical Engineering
Volume

7

Start page

473

End page

485

Subjects

Engineering, Biomedical

•

Engineering

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myoelectric prosthesis control

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targeted muscle reinnervation

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pattern-recognition control

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sensory-feedback-system

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of-the-art

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real-time

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dexterous manipulation

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amputation prostheses

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proportional control

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machine interfaces

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
TNE  
Available on Infoscience
June 19, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/179399
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