Evidence map›Paper›PMID 32543446›Full record

ArticleJMIR mHealth and uHealth2020

A Nonproprietary Movement Analysis System (MoJoXlab) Based on Wearable Inertial Measurement Units Applicable to Healthy Participants and Those With Anterior Cruciate Ligament Reconstruction Across a Range of Complex Tasks: Validation Study.

Riasat Islam, Mohamed Bennasar, Kevin Nicholas, Kate Button, Simon Holland, Paul Mulholland, Blaine Price, Mohammad Al-Amri

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 16 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Riasat IslamSchool of Computing and Communications, The Open University, Milton Keynes, United Kingdom.ORCID 0000-0002-1419-8068
Mohamed BennasarSchool of Computing and Communications, The Open University, Milton Keynes, United Kingdom.ORCID 0000-0001-8308-1632
Kevin NicholasBiomechanics and Bioengineering Research Centre Versus Arthritis, Cardiff University, Cardiff, United Kingdom.ORCID 0000-0001-6924-9291
Kate ButtonBiomechanics and Bioengineering Research Centre Versus Arthritis, Cardiff University, Cardiff, United Kingdom.ORCID 0000-0003-1073-9901
Simon HollandSchool of Computing and Communications, The Open University, Milton Keynes, United Kingdom.ORCID 0000-0002-6107-6549
Paul MulhollandKnowledge Media Institute, The Open University, Milton Keynes, United Kingdom.ORCID 0000-0001-6598-0757
Blaine PriceSchool of Computing and Communications, The Open University, Milton Keynes, United Kingdom.ORCID 0000-0002-2247-9804
Mohammad Al-AmriBiomechanics and Bioengineering Research Centre Versus Arthritis, Cardiff University, Cardiff, United Kingdom.ORCID 0000-0003-2806-0462
The Open University · GBCardiff and Vale University Health Board · GBArthritis UK · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMovement analysis in a 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 toolkits. 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.

objectiveThis paper aimed to present the validation of MoJoXlab software for using generic wearable IMUs for 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 (ACL) reconstruction.

methodsMovement data were collected from 27 healthy participants and 20 participants with ACL reconstruction. In each case, the participants wore seven MTw2 IMUs (Xsens Technologies) to monitor their movement in walking, jumping, and squatting tasks. The hip, knee, and ankle joint angles were calculated in the sagittal, frontal, and transverse planes using two different software packages: Xsens' validated proprietary MVN Analyze and MoJoXlab. The results were validated by comparing the generated waveforms, cross-correlation (CC), and normalized root mean square error (NRMSE) values.

resultsAcross all joints and activities, for data of both healthy and ACL reconstruction participants, the CC and NRMSE values for the sagittal plane are 0.99 (SD 0.01) and 0.042 (SD 0.025); 0.88 (SD 0.048) and 0.18 (SD 0.078) for the frontal plane; and 0.85 (SD 0.027) and 0.23 (SD 0.065) for the transverse plane (hip and knee joints only). On comparing the results from the two different software systems, the sagittal plane was very highly correlated, with frontal and transverse planes showing strong correlation.

conclusionsThis study demonstrates that nonproprietary software such as MoJoXlab can accurately calculate joint angles for movement analysis applications comparable with proprietary software for walking, squatting, and jumping in healthy individuals and those following ACL 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, nonproprietary 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.

Indexed as

Anterior Cruciate Ligament InjuriesAnterior Cruciate Ligament ReconstructionWearable Electronic DevicesAdultFemaleHealthy VolunteersHumansMaleReproducibility of Resultsalgorithmsanterior cruciate ligamentdigital physiotherapyexercise therapygaitkinematicslower extremitymotion trackersrange of motionwearable electronic deviceswearables

Identifiers

PMID32543446
PMCPMC7327594
OpenAlexW3014745600

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.