Automatic Classification of Knee Rehabilitation Exercises Using a Single Inertial Sensor: a Case Study

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Title: Automatic Classification of Knee Rehabilitation Exercises Using a Single Inertial Sensor: a Case Study
Authors: Bevilacqua, Antonio
Huang, Bingquan
Argent, Rob
Caulfield, Brian
Kechadi, Tahar
Permanent link: http://hdl.handle.net/10197/9947
Date: 5-Apr-2018
Online since: 2019-04-15T10:16:38Z
Abstract: Inertial measurement units have the ability to accurately record the acceleration and angular velocity of human limb segments during discrete joint movements. These movements are commonly used in exercise rehabilitation programmes following orthopaedic surgery such as total knee replacement. This provides the potential for a biofeedback system with data mining technique for patients undertaking exercises at home without physician supervision. We propose to use machine learning techniques to automatically analyse inertial measurement unit data collected during these exercises, and then assess whether each repetition of the exercise was executed correctly or not. Our approach consists of two main phases: signal segmentation, and segment classification. Accurate pre-processing and feature extraction are paramount topics in order for the technique to work. In this paper, we present a classification method for unsupervised rehabilitation exercises, based on a segmentation process that extracts repetitions from a longer signal activity. The results obtained from experimental datasets of both clinical and healthy subjects, for a set of 4 knee exercises commonly used in rehabilitation, are very promising.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: IEEE
Copyright (published version): 2018 IEEE
Keywords: Feature extractionBiological control systemsKneeSurgeryAndroidsHumanoid robotsMeasurement units
DOI: 10.1109/BSN.2018.8329649
Other versions: https://bhi-bsn.embs.org/2018/
https://ieeexplore.ieee.org/document/8329649
Language: en
Status of Item: Peer reviewed
Is part of: 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN)
Conference Details: IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN), 4-7 March 2018, Las Vegas, Nevada, USA
ISBN: 978-1-5386-1110-4
Appears in Collections:Insight Research Collection

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