Toward higher-performance bionic limbs for wider clinical use
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
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.
Date Issued
2023-04-01
Date Acceptance
2021-04-01
Citation
Nature Biomedical Engineering, 2023, 7, pp.473-485
ISSN
2157-846X
Publisher
Nature Research
Start Page
473
End Page
485
Journal / Book Title
Nature Biomedical Engineering
Volume
7
Copyright Statement
© Springer Nature Limited 2021. The final publication is available at Springer via https://doi.org/10.1038/s41551-021-00732-x
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000656399300002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
AMPUTATION PROSTHESES
DEXTEROUS MANIPULATION
Engineering
Engineering, Biomedical
MACHINE INTERFACES
MYOELECTRIC PROSTHESIS CONTROL
OF-THE-ART
PATTERN-RECOGNITION CONTROL
PROPORTIONAL CONTROL
REAL-TIME
Science & Technology
SENSORY-FEEDBACK-SYSTEM
TARGETED MUSCLE REINNERVATION
Technology
Publication Status
Published
Date Publish Online
2021-05-31