Automatic identification of gait events using an instrumented sock

PREECE, S.J., KENNEY, L.P.J., MAJOR, J.M., DIAS, T., LAY, E. and FERNANDES, B.T., 2011. Automatic identification of gait events using an instrumented sock. Journal of NeuroEngineering and Rehabilitation, 8 (32), pp. 1-10.

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Abstract

Background: Textile-based transducers are an emerging technology in which piezo-resistive properties of materials are used to measure an applied strain. By incorporating these sensors into a sock, this technology offers the potential to detect critical events during the stance phase of the gait cycle. This could prove useful in several applications, such as functional electrical stimulation (FES) systems to assist gait. Methods: We investigated the output of a knitted resistive strain sensor during walking and sought to determine the degree of similarity between the sensor output and the ankle angle in the sagittal plane. In addition, we investigated whether it would be possible to predict three key gait events, heel strike, heel lift and toe off, with a relatively straight-forward algorithm. This worked by predicting gait events to occur at fixed time offsets from specific peaks in the sensor signal. Results: Our results showed that, for all subjects, the sensor output exhibited the same general characteristics as the ankle joint angle. However, there were large between-subjects differences in the degree of similarity between the two curves. Despite this variability, it was possible to accurately predict gait events using a simple algorithm. This algorithm displayed high levels of trial-to-trial repeatability. Conclusions: This study demonstrates the potential of using textile-based transducers in future devices that provide active gait assistance.

Item Type: Journal article
Publication Title: Journal of NeuroEngineering and Rehabilitation
Creators: Preece, S.J., Kenney, L.P.J., Major, J.M., Dias, T., Lay, E. and Fernandes, B.T.
Publisher: BioMed Central/Springer
Place of Publication: London
Date: 2011
Volume: 8
Number: 32
Identifiers:
NumberType
10.1186/1743-0003-8-32DOI
Rights: © 2011 BioMed Central Ltd. Part of Springer Science+Business Media.
Divisions: Schools > School of Art and Design
Depositing User: EPrints Services
Date Added: 09 Oct 2015 10:10
Last Modified: 23 Aug 2016 09:08
URI: http://irep.ntu.ac.uk/id/eprint/8835

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