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Non-proprietary movement analysis software using wearable inertial measurement units on both healthy participants and those with anterior cruciate ligament reconstruction across a range of complex tasks: validation study

Islam, Riasat; Bennasar, Mohamed; Nicholas, Kevin; Button, Kate; Holland, Simon; Mulholland, Paul; Price, Blaine and Al-Amri, Mohammad (2020). Non-proprietary movement analysis software using wearable inertial measurement units on both healthy participants and those with anterior cruciate ligament reconstruction across a range of complex tasks: validation study. JMIR Mhealth Uhealth (Early access).

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DOI (Digital Object Identifier) Link: https://doi.org/10.2196/17872
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Abstract

Background:
Movement analysis in the clinical setting is frequently restricted to observational methods to inform clinical decision making, which has limited accuracy. Fixed-site optical expensive movement analysis laboratories provide ‘gold-standard’ kinematic measurements, however they are rarely accessed for routine clinical use. Wearable inertial measurement units (IMUs) have been demonstrated as comparable, inexpensive and portable movement analysis toolkit. MoJoXlab has therefore been developed to work with generic wearable IMUs. However, before using MoJoXlab in clinical practice there is a need to establish its validity in participants with and without knee conditions across a range of tasks with varying complexity.

Objective:
This paper presents the validation of MoJoXlab software for using generic wearable IMUs in calculating hip, knee and ankle joint angle measurements in the sagittal, frontal and transverse planes, for walking, squatting and jumping in healthy participants and those with anterior cruciate ligament reconstruction.

Methods:
Movement data were collected from 27 healthy participants and 20 participants with Anterior Cruciate Ligament (ACL) reconstruction. In each case, participants wore seven ‘MTw2’ IMUs to monitor their movement in walking, jumping and squatting tasks. Hip, knee and ankle joint angles were calculated in the sagittal, frontal and transverse plane using two different software packages: Xsens’s validated proprietary MVN Analyze, and MoJoXlab. Results were validated by comparing the generated waveforms, cross-correlation (CC) and normalized root mean square error (NRMSE) values.

Results:
Across all joints and activities, for both healthy and ACL reconstruction data, the cross-correlation and normalized root mean square error for the sagittal plane are: 0.99 ± 0.01 and 0.042 ± 0.025 respectively; for the frontal plane: 0.88 ± 0.048 and 0.18 ± 0.078; and for the transverse plane (hip and knee joints only): 0.85 ± 0.027 and 0.23 ± 0.065. On comparing results from the two different software systems, the sagittal plane is very highly correlated, with frontal and transverse planes showing strong correlation.

Conclusions:
This paper demonstrates that non-proprietary software such as MoJoXlab can accurately calculate joint angles for movement analysis applications comparable to proprietary software, for walking, squatting and jumping, in healthy individuals and those following anterior cruciate ligament reconstruction. MoJoXlab can be used with generic wearable IMUs that can provide clinicians accurate objective data when assessing patients’ movement, even when changes are too small to be observed visually. The availability of easy-to-setup, non-proprietary software for calibration, data collection and joint angle calculation has the potential to increase the adoption of wearable IMU sensors in clinical practice, as well as in free living conditions, and may provide wider access to accurate, objective assessment of patients’ progress over time.

Item Type: Journal Item
Copyright Holders: 2020 The Authors
Project Funding Details:
Funded Project NameProject IDFunding Body
Not Set18461Versus Arthritis
Not SetNot SetGoldcrest Charitable Trust
Not SetEP/P01013X/1EPSRC
Not SetEP/R033862/1EPSRC
Not SetEP/R013144/1EPSRC
Keywords: physiotherapy; wearables; inertial sensors; IMU; joint angles; biomechanics; validation; software; movement analysis;
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Research Group: Centre for Research in Computing (CRC)
Item ID: 69997
Depositing User: Riasat Islam
Date Deposited: 31 Mar 2020 16:16
Last Modified: 17 Apr 2020 11:33
URI: http://oro.open.ac.uk/id/eprint/69997
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