Reflex control of robotic gait using human walking data

Macleod, C. A., Meng, L., Conway, B. and Porr, B. (2014) Reflex control of robotic gait using human walking data. PLoS ONE, 9(10), e109959. (doi:10.1371/journal.pone.0109959) (PMID:25347544) (PMCID:PMC4210155)

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Publisher's URL: http://dx.doi.org/10.1371/journal.pone.0109959

Abstract

Control of human walking is not thoroughly understood, which has implications in developing suitable strategies for the retraining of a functional gait following neurological injuries such as spinal cord injury (SCI). Bipedal robots allow us to investigate simple elements of the complex nervous system to quantify their contribution to motor control. RunBot is a bipedal robot which operates through reflexes without using central pattern generators or trajectory planning algorithms. Ground contact information from the feet is used to activate motors in the legs, generating a gait cycle visually similar to that of humans. Rather than developing a more complicated biologically realistic neural system to control the robot's stepping, we have instead further simplified our model by measuring the correlation between heel contact and leg muscle activity (EMG) in human subjects during walking and from this data created filter functions transferring the sensory data into motor actions. Adaptive filtering was used to identify the unknown transfer functions which translate the contact information into muscle activation signals. Our results show a causal relationship between ground contact information from the heel and EMG, which allows us to create a minimal, linear, analogue control system for controlling walking. The derived transfer functions were applied to RunBot II as a proof of concept. The gait cycle produced was stable and controlled, which is a positive indication that the transfer functions have potential for use in the control of assistive devices for the retraining of an efficient and effective gait with potential applications in SCI rehabilitation.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Porr, Dr Bernd and Meng, Miss Lin and Conway, Prof Bernard
Authors: Macleod, C. A., Meng, L., Conway, B., and Porr, B.
Subjects:R Medicine > R Medicine (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
College/School:College of Science and Engineering > School of Engineering > Biomedical Engineering
Journal Name:PLoS ONE
Publisher:Public Library of Science
ISSN:1932-6203
Copyright Holders:Copyright © 2014 The Authors
First Published:First published in PLoS ONE 9(10):e109959
Publisher Policy:Reproduced under a Creative Commons License
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