The future of bionic limbs: the untapped synergy of signal processing, control, and wireless connectivity
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
The flexibility and dexterity of human limbs rely on the processing of a vast quantity of signals within the sensory-motor networks in the brain and spinal cord, distilled into stimuli that govern the commands and movements. Hence, the use of assistive devices, such as robotic limbs or exoskeletons, is critically dependent on the processing of a large number of heterogeneous signals to mimic natural movements. This article provides a panoramic overview of the three paradigms for the control of bionic limbs based on mechatronic technology. Two of them have already been established in the literature, while the third one, advocated by this article, is an emerging approach, enabled by the latest developments in connectivity and computation. In the first paradigm, the bionic limbs rely on conventional control and are directly reconnected to the human sensory-motor system, which requires a large signal processing bandwidth. The second paradigm is based on semiautonomous limbs, endowed with context-aware processing and certain decision capability. Following the advances in wireless connectivity and cloud/edge processing, this article introduces a third paradigm of connected limbs.
Date Issued
2024-07-01
Date Acceptance
2024-10-01
Citation
IEEE Signal Processing Magazine, 2024, 41 (4), pp.58-75
ISSN
1053-5888
Publisher
Institute of Electrical and Electronics Engineers
Start Page
58
End Page
75
Journal / Book Title
IEEE Signal Processing Magazine
Volume
41
Issue
4
Copyright Statement
Copyright © 2024 IEEE. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Subjects
Assistive devices
Bandwidth
Engineering
Engineering, Electrical & Electronic
Exoskeletons
Mechatronics
Robot sensing systems
Science & Technology
Signal processing
Spinal cord
Technology
Wireless communication
Wireless sensor networks
Publication Status
Published
Date Publish Online
2024-10-11