Scoring Performance on the Y-Balance Test

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Title: Scoring Performance on the Y-Balance Test
Authors: Mahato, VivekJohnston, WilliamCunningham, Pádraig
Permanent link: http://hdl.handle.net/10197/12287
Date: 9-Aug-2019
Online since: 2021-06-22T15:42:11Z
Abstract: The Y-Balance Test (YBT) is a dynamic balance assessment commonly used in sports medicine. In this research we explore how data from a wearable sensor can provide further insights from YBT performance. We do this in a Case-Based Reasoning (CBR) framework where the assessment of similarity on the wearable sensor data is the key challenge. The assessment of similarity on time-series data is not a new topic in CBR research; however the focus here is on working as close to the raw time-series as possible so that no information is lost. We report results on two aspects, the assessment of YBT performance and the insights that can be drawn from comparisons between pre- and post- injury performance.
Funding Details: European Commission - European Regional Development Fund
Science Foundation Ireland
Type of material: Conference Publication
Publisher: Springer
Series/Report no.: Lecture Notes in Computer Science; 11680
Copyright (published version): 2019 Springer
Keywords: Wearable sensorsY balance testTime series data
DOI: 10.1007/978-3-030-29249-2_19
Other versions: https://iccbr2019.com/
Language: en
Status of Item: Peer reviewed
Conference Details: The 27th International Conference (ICCBR 2019), Otzenhausen, Germany, 8-12 September 2019
ISBN: 978-3-030-29249-2
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science Research Collection
I-Form Research Collection

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