Naeem, A., Rizwan, M., Farhan Maqbool, H. et al. (4 more authors) (Cover date: March 2022) Virtual constraint control of Knee-Ankle prosthesis using an improved estimate of the thigh phase-variable. Biomedical Signal Processing and Control, 73. 103366. ISSN 1746-8094
Abstract
In the human gait cycle, virtual constraints enforce a robust relationship between the thigh phase-variable and the knee/ankle angle. These constraints enable an accurate estimation and control of angular trajectory when the input phase-variable profile is low in gait aperiodicity and sensor noise. In this work, we present discrete Fourier transform (DFT) based virtual constraint schemes for estimating the knee/ankle trajectories using an improved monotonic and linear trajectory of the thigh phase-variable. To minimize the likely aberrations in the desired trajectory of the phase-variable, the contour of the thigh angle and its integral is amplitude scaled, time shifted, and interpolated over the complete stride. The processed contour is then refitted to an ideal circle using polynomial optimization via two different schemes. For both proposed schemes, estimated knee/ankle trajectories are compared with the benchmark gait kinematics of healthy persons and an amputee wearing three commercial prostheses. Simulation results, based on realistic prosthesis actuator parameters, show a 2.18 ± 0.83 times reduction in the mean trajectory tracking error for three contrasting walking speeds, validating the efficacy of proposed schemes.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | Virtual constraint control; Phase-variable; Active prosthesis; Knee; ankle prosthesis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 Aug 2023 10:30 |
Last Modified: | 23 Aug 2023 10:30 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.bspc.2021.103366 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202667 |