Bertuletti, S., Salis, F., Cereatti, A. et al. (5 more authors) (2019) Inter-leg distance measurement as a tool for accurate step counting in patients with multiple sclerosis. In: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 23-27 Jul 2019, Berlin, Germany. IEEE , pp. 6413-6417. ISBN 9781538613122
Abstract
Step detection is commonly performed using wearable inertial devices. However, methods based on the extraction of signals features may deteriorate their accuracy when applied to very slow walkers with abnormal gait patterns. The aim of this study is to test and validate an innovative step counter method (DiSC) based on the direct measurement of inter-leg distance. Data were recorded using an innovative wearable system which integrates a magneto-inertial unit and multiple distance sensors (DSs) attached to the shank. The method allowed for the detection of both left and right steps using a single device and was validated on thirteen people affected by multiple sclerosis (0 < EDSS < 6.5) while performing a six-minute walking test. Two different measurement ranges for the distance sensor were tested (DS 200 : 0–200 mm; DS 400 : 0–400 mm). Accuracy was evaluated by comparing the estimates of the DiSC method against video recordings used as gold standard. Preliminary results showed a good accuracy in detecting steps with half the errors in detecting the step of the instrumented side compared to the non-instrumented (mean absolute percentage error 2.4% vs 4.8% for DS 200 ; mean absolute percentage error 2% vs 5.4% for DS 400 ). When averaging errors across patients, over and under estimation errors were compensated, and very high accuracy was achieved (E % <1.2% for DS 200 ; E % <0.7% for DS 400 ). DS 400 is the suggested configuration for patients walking with a large base of support.
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 users, 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 components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Science Research Council (EPSRC) EP/K03877X/1; EP/S032940/1 National Institute for Health Research IS-BRC-1215-20017 European Commission - Horizon 2020 820820 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Oct 2019 08:54 |
Last Modified: | 07 Oct 2020 00:38 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/embc.2019.8857353 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:152254 |