Rehabilitation exercise assessment using inertial sensors: a cross-sectional analytical study

Files in This Item:
File Description SizeFormat 
insight_publication.pdf314.15 kBAdobe PDFDownload
Title: Rehabilitation exercise assessment using inertial sensors: a cross-sectional analytical study
Authors: Giggins, Oonagh M.
Sweeney, Kevin T.
Caulfield, Brian
Permanent link:
Date: 27-Nov-2014
Online since: 2015-03-18T09:49:42Z
Abstract: Background: Accurate assessments of adherence and exercise performance are required in order to ensure that patients adhere to and perform their rehabilitation exercises correctly within the home environment. Inertial sensors have previously been advocated as a means of achieving these requirements, by using them as an input to an exercise biofeedback system. This research sought to investigate whether inertial sensors, and in particular a single sensor, can accurately classify exercise performance in patients performing lower limb exercises for rehabilitation purposes. Methods:Fifty-eight participants (19 male, 39 female, age: 53.9 +/- 8.5 years, height: 1.69 +/- 0.08 m, weight: 74.3 +/- 13.0 kg) performed ten repetitions of seven lower limb exercises (hip abduction, hip flexion, hip extension, knee extension, heel slide, straight leg raise, and inner range quadriceps). Three inertial sensor units, secured to the thigh, shin and foot of the leg being exercised, were used to acquire data during each exercise. Machine learning classification methods were applied to quantify the acquired data. Results:The classification methods achieved relatively high accuracy at distinguishing between correct and incorrect performance of an exercise using three, two, or one sensor while moderate efficacy scores were also achieved by the classifier when attempting to classify the particular error in exercise performance. Results also illustrated that a reduction in the number of inertial sensor units employed has little effect on the overall efficacy results. Conclusion:The results revealed that it is possible to classify lower limb exercise performance using inertial sensors with satisfactory levels of accuracy and reducing the number of sensors employed does not reduce the accuracy of the method
Type of material: Journal Article
Publisher: BioMed Central
Journal: Journal of NeuroEngineering Rehabilitation
Volume: 11
Issue: 158
Start page: 1
End page: 10
Copyright (published version): 2014 the Authors
Keywords: Personal sensingInertial sensorsRehabilitationExercisePerformance classification
DOI: 10.1186/1743-0003-11-158
Language: en
Status of Item: Peer reviewed
Appears in Collections:Public Health, Physiotherapy and Sports Science Research Collection
Insight Research Collection

Show full item record

Citations 10

Last Week
Last month
checked on Feb 11, 2019

Google ScholarTM



This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.