Applied Bionics and Biomechanics

Applied Bionics and Biomechanics / 2012 / Article

Open Access

Volume 9 |Article ID 801859 | https://doi.org/10.3233/ABB-2012-0057

M. S. Huq, M. O. Tokhi, "Genetic Algorithms Based Approach for Designing Spring Brake Orthosis – Part I: Spring Parameters", Applied Bionics and Biomechanics, vol. 9, Article ID 801859, 14 pages, 2012. https://doi.org/10.3233/ABB-2012-0057

Genetic Algorithms Based Approach for Designing Spring Brake Orthosis – Part I: Spring Parameters

Abstract

Spring brake orthosis (SBO) concentrates purely on the knee to generate the swing phase of the paraplegic gait with the required hip flexion occurring passively as a consequence of the ipsilateral knee flexion, generated by releasing the torsion spring mounted at the knee joint. Electrical stimulation then drives the knee back to full extension, as well as restores the spring potential energy. In this paper, genetic algorithm (GA) and its variant multi-objective GA (MOGA) is used to perform the search operation for the ‘best’ spring parameters for the SBO spring mounted on an average sized subject simulated in the sagittal plane. Conventional torsion spring is tested against constant torque type spring in terms of swing duration as, based on first principles, it is hypothesized that constant torque spring would be able to produce slower SBO swing phase as might be preferred in assisted paraplegic gait. In line with the hypothesis, it is found that it is not possible to delay the occurrence of the flexion peak of the SBO swing phase further than its occurrence in the natural gait. The use of conventional torsion spring causes the swing knee flexion peak to appear rather faster than that of the natural gait, resulting in a potentially faster swing phase and hence gait cycle. The constant torque type spring on the other hand is able to stretch duration of the swing phase to some extent, rendering it the preferable spring type in SBO.

Copyright © 2012 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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