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  5. Evaluating Performance of the Lunge Exercise with Multiple and Individual Inertial Measurement Units
 
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Evaluating Performance of the Lunge Exercise with Multiple and Individual Inertial Measurement Units

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Author(s)
Whelan, Darragh 
O'Reilly, Martin 
Ward, Tomás 
Delahunt, Eamonn 
Caulfield, Brian 
Uri
http://hdl.handle.net/10197/7876
Date Issued
19 May 2016
Date Available
06T11:41:49Z September 2016
Abstract
The lunge is an important component of lower limb rehabilitation, strengthening and injury risk screening. Completing the movement incorrectly alters muscle activation and increases stress on knee, hip and ankle joints. This study sought to investigate whether IMUs are capable of discriminating between correct and incorrect performance of the lunge. Eighty volunteers (57 males, 23 females, age: 24.68± 4.91 years, height: 1.75± 0.094m, body mass: 76.01±13.29kg) were fitted with five IMUs positioned on the lumbar spine, thighs and shanks. They then performed the lunge exercise with correct form and 11 specific deviations from acceptable form. Features were extracted from the labelled sensor data and used to train and evaluate random-forests classifiers. The system achieved 83% accuracy, 62% sensitivity and 90% specificity in binary classification with a single sensor placed on the right thigh and 90% accuracy, 80% sensitivity and 92% specificity using five IMUs. This multi-sensor set up can detect specific deviations with 70% accuracy. These results indicate that a single IMU has the potential to differentiate between correct and incorrect lunge form and using multiple IMUs adds the possibility of identifying specific deviations a user is making when completing the lunge.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Copyright (Published Version)
2016 ACM
Keywords
  • Personal sensing

  • Exercise

  • Classification

  • Inertial Measurement ...

  • Lunge

  • Functional screening ...

  • Biofeedback

  • Rehabilitation

Web versions
http://pervasivehealth.org/2016/show/home
Language
English
Status of Item
Peer reviewed
Description
Pervasive Health 2016: 10th EAI International Conference on Pervasive Computing Technologies for Healthcare, Cancun, Mexico, 16-19 May 2016
ISBN
978-1-63190-051-8
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Insight Research Collection
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