Real-time interface algorithm for ankle kinematics and stiffness from electromyographic signals
Author(s)
Dimitrov, Hristo
Bull, Anthony MJ
Farina, Dario
Type
Journal Article
Abstract
Shortcomings in capabilities of below-knee (transtibial) prostheses, compared to their biological counterparts, still cause medical complications and functional deficit to millions of amputees around the world. Although active (powered actuation) transtibial prostheses have the potential to bridge these gaps, the current control solutions limit their efficacy. Here we describe the development of a novel interface for two degrees-of-freedom position and stiffness control for below-knee amputees. The developed algorithm for the interface relies entirely on muscle electrical signals from the lower leg. The algorithm was tested for voluntary position and stiffness control in eight able-bodied and two transtibial amputees and for voluntary stiffness control with foot position estimation while walking in eight able-bodied and one transtibial amputee. The results of the voluntary control experiment demonstrated a promising target reaching success rate, higher for amputees compared to the able-bodied individuals (82.5% and 72.5% compared to 72.5% and 68.1% for the position and position and stiffness matching tasks respectively). Further, the algorithm could provide the means to control four stiffness levels during walking in both amputee and able-bodied individuals while providing estimates of foot kinematics (gait cycle cross-correlation >75% for the sagittal and >90% for the frontal plane and gait cycle root mean square error <7.5° in sagittal and <3° in frontal plane for able-bodied and amputee individuals across three walking speeds). The results from the two experiments demonstrate the feasibility of using this novel algorithm for online control of multiple degrees of freedom and of their stiffness in lower limb prostheses.
Date Issued
2020-04-13
Date Acceptance
2020-04-04
Citation
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020, 28 (6), pp.1416-1427
ISSN
1534-4320
Publisher
Institute of Electrical and Electronics Engineers
Start Page
1416
End Page
1427
Journal / Book Title
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume
28
Issue
6
Copyright Statement
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Engineering and Physical Sciences Research Council
Identifier
https://ieeexplore.ieee.org/document/9062607
Grant Number
EP/R512540/1
Subjects
0903 Biomedical Engineering
0906 Electrical and Electronic Engineering
Biomedical Engineering
Publication Status
Published
Date Publish Online
2020-04-09