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Sensor-based postural feedback is more effective than conventional feedback to improve lumbopelvic movement control in patients with chronic low back pain: a randomised controlled trial

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, September 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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1 blog
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Citations

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31 Dimensions

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229 Mendeley
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Title
Sensor-based postural feedback is more effective than conventional feedback to improve lumbopelvic movement control in patients with chronic low back pain: a randomised controlled trial
Published in
Journal of NeuroEngineering and Rehabilitation, September 2018
DOI 10.1186/s12984-018-0423-6
Pubmed ID
Authors

Thomas Matheve, Simon Brumagne, Christophe Demoulin, Annick Timmermans

Abstract

Improving movement control can be an important treatment goal for patients with chronic low back pain (CLBP). Although external feedback is essential when learning new movement skills, many aspects of feedback provision in patients with CLBP remain currently unexplored. New rehabilitation technologies, such as movement sensors, are able to provide reliable and accurate feedback. As such, they might be more effective than conventional feedback for improving movement control. The aims of this study were (1) to assess whether sensor-based feedback is more effective to improve lumbopelvic movement control compared to feedback from a mirror or no feedback in patients with chronic low back pain (CLBP), and (2) to evaluate whether patients with CLBP are equally capable of improving lumbopelvic movement control compared to healthy persons. Fifty-four healthy participants and 54 patients with chronic non-specific LBP were recruited. Both participant groups were randomised into three subgroups. During a single exercise session, subgroups practised a lumbopelvic movement control task while receiving a different type of feedback, i.e. feedback from movement sensors, from a mirror or no feedback (=control group). Kinematic measurements of the lumbar spine and hip were obtained at baseline, during and immediately after the intervention to evaluate the improvements in movement control on the practised task (assessment of performance) and on a transfer task (assessment of motor learning). Sensor-based feedback was more effective than feedback from a mirror (p < 0.0001) and no feedback (p < 0.0001) to improve lumbopelvic movement control performance (Sensor vs. Mirror estimated difference 9.9° (95% CI 6.1°-13.7°), Sensor vs. Control estimated difference 10.6° (95% CI 6.8°-14.3°)) and motor learning (Sensor vs. Mirror estimated difference 7.2° (95% CI 3.8°-10.6°), Sensor vs. Control estimated difference 6.9° (95% CI 3.5°-10.2°)). Patients with CLBP were equally capable of improving lumbopelvic movement control compared to healthy persons. Sensor-based feedback is an effective means to improve lumbopelvic movement control in patients with CLBP. Future research should focus on the long-term retention effects of sensor-based feedback. clinicaltrials.gov NCT02773160 , (retrospectively registered on May 16th, 2016).

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 229 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 229 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 33 14%
Student > Bachelor 32 14%
Researcher 18 8%
Student > Ph. D. Student 18 8%
Other 17 7%
Other 30 13%
Unknown 81 35%
Readers by discipline Count As %
Nursing and Health Professions 51 22%
Medicine and Dentistry 37 16%
Sports and Recreations 18 8%
Engineering 11 5%
Neuroscience 6 3%
Other 23 10%
Unknown 83 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 21 February 2019.
All research outputs
#2,283,038
of 23,103,903 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#100
of 1,294 outputs
Outputs of similar age
#50,223
of 341,556 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#1
of 28 outputs
Altmetric has tracked 23,103,903 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,294 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,556 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.