How Many Steps to Represent Individual Gait?

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Title: How Many Steps to Represent Individual Gait?
Authors: Ader, Lilian Genaro MottiMcManus, KillianGreene, Barry R.Caulfield, Brian
Permanent link: http://hdl.handle.net/10197/12219
Date: 26-Jun-2020
Online since: 2021-05-27T11:15:36Z
Abstract: Assessing and reproducing user's mobility has multiple purposes for interactive systems. In particular, the quantification of gait parameters has been used for user modelling, virtual environments, and augmented reality. While many technologies can be used to assess gait, measuring spatio-temporal parameters and their fluctuations, it is important to evaluate how many steps are necessary to represent the gait pattern of an individual, in order to provide better feedback to the user and improve user experience. In this preliminary study, we evaluate the intra-session reliability of spatio-temporal gait parameters for 24 healthy adults walking two trials of 15m in a corridor. Angular velocity data were acquired from body-worn inertial measurement units attached to participants' right and left shanks. An adaptive algorithm was applied for gait event detection, and gait parameters were analyzed according to pre-defined numbers of steps extracted from the full length of the trial. The main contribution of the present analysis is to present a method of gait event detection, segmentation and analysis that can be used for adjusting interactive systems to individual users.
Funding Details: Science Foundation Ireland
Funding Details: Insight Research Centre
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2020 ACM
Keywords: Personal sensingGait analysisReliabilityMotion-based interactionWalking
DOI: 10.1145/3393672.3398638
Other versions: https://eics.acm.org/2020/
Language: en
Status of Item: Peer reviewed
Conference Details: The 12th ACM SIGCHI Symposium on Engineering Interactive Computer Systems, Sophia-Antipolis, France, 23-26 June 2020
ISBN: 978-1-4503-7984-7/20/06
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Public Health, Physiotherapy and Sports Science Research Collection
Insight Research Collection

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