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Markerless motion capture systems as training device in neurological rehabilitation: a systematic review of their use, application, target population and efficacy

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, June 2017
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Title
Markerless motion capture systems as training device in neurological rehabilitation: a systematic review of their use, application, target population and efficacy
Published in
Journal of NeuroEngineering and Rehabilitation, June 2017
DOI 10.1186/s12984-017-0270-x
Pubmed ID
Authors

Els Knippenberg, Jonas Verbrugghe, Ilse Lamers, Steven Palmaers, Annick Timmermans, Annemie Spooren

Abstract

Client-centred task-oriented training is important in neurological rehabilitation but is time consuming and costly in clinical practice. The use of technology, especially motion capture systems (MCS) which are low cost and easy to apply in clinical practice, may be used to support this kind of training, but knowledge and evidence of their use for training is scarce. The present review aims to investigate 1) which motion capture systems are used as training devices in neurological rehabilitation, 2) how they are applied, 3) in which target population, 4) what the content of the training and 5) efficacy of training with MCS is. A computerised systematic literature review was conducted in four databases (PubMed, Cinahl, Cochrane Database and IEEE). The following MeSH terms and key words were used: Motion, Movement, Detection, Capture, Kinect, Rehabilitation, Nervous System Diseases, Multiple Sclerosis, Stroke, Spinal Cord, Parkinson Disease, Cerebral Palsy and Traumatic Brain Injury. The Van Tulder's Quality assessment was used to score the methodological quality of the selected studies. The descriptive analysis is reported by MCS, target population, training parameters and training efficacy. Eighteen studies were selected (mean Van Tulder score = 8.06 ± 3.67). Based on methodological quality, six studies were selected for analysis of training efficacy. Most commonly used MCS was Microsoft Kinect, training was mostly conducted in upper limb stroke rehabilitation. Training programs varied in intensity, frequency and content. None of the studies reported an individualised training program based on client-centred approach. Motion capture systems are training devices with potential in neurological rehabilitation to increase the motivation during training and may assist improvement on one or more International Classification of Functioning, Disability and Health (ICF) levels. Although client-centred task-oriented training is important in neurological rehabilitation, the client-centred approach was not included. Future technological developments should take up the challenge to combine MCS with the principles of a client-centred task-oriented approach and prove efficacy using randomised controlled trials with long-term follow-up. Prospero registration number 42016035582 .

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Mendeley readers

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The data shown below were compiled from readership statistics for 361 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 361 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 58 16%
Student > Master 49 14%
Student > Bachelor 43 12%
Researcher 25 7%
Student > Doctoral Student 17 5%
Other 50 14%
Unknown 119 33%
Readers by discipline Count As %
Nursing and Health Professions 48 13%
Engineering 44 12%
Medicine and Dentistry 42 12%
Computer Science 19 5%
Neuroscience 19 5%
Other 57 16%
Unknown 132 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 June 2017.
All research outputs
#15,871,137
of 23,576,969 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#860
of 1,314 outputs
Outputs of similar age
#199,888
of 316,740 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#16
of 23 outputs
Altmetric has tracked 23,576,969 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,314 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
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We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.