A robust walking detection algorithm using a single foot-worn inertial sensor: validation in real-life settings

Abstract

Walking activity and gait parameters are considered among the most relevant mobility-related parameters. Currently, gait assessments have been mainly analyzed in laboratory or hospital settings, which only partially reflect usual performance (i.e., real world behavior). In this study, we aim to validate a robust walking detection algorithm using a single foot-worn inertial measurement unit (IMU) in real-life settings. We used a challenging dataset including 18 individuals performing free-living activities. A multi-sensor wearable system including pressure insoles, multiple IMUs, and infrared distance sensors (INDIP) was used as reference. Accurate walking detection was obtained, with sensitivity and specificity of 98 and 91% respectively. As robust walking detection is needed for ambulatory monitoring to complete the processing pipeline from raw recorded data to walking/mobility outcomes, a validated algorithm would pave the way for assessing patient performance and gait quality in real-world conditions.

Metadata

Item Type:	Article
Authors/Creators:	Prigent, G. https://orcid.org/0000-0003-1618-4054 Aminian, K. Cereatti, A. Salis, F. Bonci, T. https://orcid.org/0000-0002-8255-4730 Scott, K. Mazzà, C. Alcock, L. Del Din, S. Gazit, E. Hansen, C. Paraschiv-Ionescu, A.
Copyright, Publisher and Additional Information:	© 2023 The Authors. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords:	Adaptive threshold; Continuous wavelet transform; Foot-worn sensor; Real-world; Walking detection
Dates:	Published: September 2023 Published (online): 18 April 2023 Accepted: 8 March 2023
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Depositing User:	Symplectic Sheffield
Date Deposited:	05 Jun 2023 11:30
Last Modified:	15 Aug 2023 03:17
Status:	Published
Publisher:	Springer Science and Business Media LLC
Refereed:	Yes
Identification Number:	10.1007/s11517-023-02826-x
Related URLs:	PubMed URL
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:199673

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A robust walking detection algorithm using a single foot-worn inertial sensor: validation in real-life settings

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