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  5. Scoring Performance on the Y-Balance Test
 
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Scoring Performance on the Y-Balance Test

Author(s)
Mahato, Vivek  
Johnston, William  
Cunningham, Pádraig  
Uri
http://hdl.handle.net/10197/12287
Date Issued
2019-08-09
Date Available
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.
Sponsorship
European Commission - European Regional Development Fund
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
Springer
Series
Lecture Notes in Computer Science
11680
Copyright (Published Version)
2019 Springer
Subjects

Wearable sensors

Y balance test

Time series data

DOI
10.1007/978-3-030-29249-2_19
Web versions
https://iccbr2019.com/
Language
English
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/
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Scoring Performance on the Y-Balance Test.pdf

Size

1.19 MB

Format

Adobe PDF

Checksum (MD5)

b826d1ecb4b377d15c18fe8e97bc1212

Owning collection
I-Form Research Collection
Mapped collections
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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