Martinez-Hernandez, U, Rubio-Solis, A, Cedeno-Campos, V et al. (1 more author) (2019) Towards an intelligent wearable ankle robot for assistance to foot drop. In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), 06-09 Oct 2019, Bari, Italy. IEEE , pp. 3410-3415. ISBN 9781728145693
Abstract
A wearable ankle robot prototype for assistance to foot drop is presented in this work. This device is built with soft and hard materials and employs one inertial sensor. First, the ankle robot uses a high-level method, developed with a Bayesian formulation, for recognition of walking activities and gait periods. Second, a low-level method, with a proportional-integral-derivative controller (PID), controls the wearable device to operate in assistive and transparent modes. In an assistive mode, activated by the toe-off detection, the wearable device assists the human foot in dorsiflexion orientation to reduce the effect of foot drop abnormality. In a transparent mode, activated by the heel-contact detection, the robot device follows the movements performed by the human foot. The wearable prototype is validated with experiments, in simulation and real-time modes, for recognition of walking activity and control of assistive and transparent modes during walking. Experiments achieved 99.87% and 99.20% accuracies for recognition of walking activity and gait periods. Results also show the ability of the wearable robot to operate according to the gait period recognised during walking. Overall, this work offers a wearable robot prototype with the potential to assist the human foot during walking, which is important to allow subjects to recover their confidence and quality of life.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 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. |
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: | 21 Apr 2021 15:12 |
Last Modified: | 26 May 2021 15:34 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/smc.2019.8914170 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:173145 |