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Quantification of upper limb position sense using an exoskeleton and a virtual reality display

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, March 2018
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Title
Quantification of upper limb position sense using an exoskeleton and a virtual reality display
Published in
Journal of NeuroEngineering and Rehabilitation, March 2018
DOI 10.1186/s12984-018-0367-x
Pubmed ID
Authors

Anne Deblock-Bellamy, Charles Sebiyo Batcho, Catherine Mercier, Andreanne K. Blanchette

Abstract

Proprioceptive sense plays a significant role in the generation and correction of skilled movements and, consequently, in most activities of daily living. We developed a new proprioception assessment protocol that enables the quantification of elbow position sense without using the opposite arm, involving active movement of the evaluated limb or relying on working memory. The aims of this descriptive study were to validate this assessment protocol by quantifying the elbow position sense of healthy adults, before using it in individuals who sustained a stroke, and to investigate its test-retest reliability. Elbow joint position sense was quantified using a robotic device and a virtual reality system. Two assessments were performed, by the same evaluator, with a one-week interval. While the participant's arms and hands were occluded from vision, the exoskeleton passively moved the dominant arm from an initial to a target position. Then, a virtual arm representation was projected on a screen placed over the participant's arm. This virtual representation and the real arm were not perfectly superimposed, however. Participants had to indicate verbally the relative position of their arm (more flexed or more extended; two-alternative forced choice paradigm) compared to the virtual representation. Each participant completed a total of 136 trials, distributed in three phases. The angular differences between the participant's arm and the virtual representation ranged from 1° to 27° and changed pseudo-randomly across trials. No feedback about results was provided to the participants during the task. A discrimination threshold was statistically extracted from a sigmoid curve fit representing the relationship between the angular difference and the percentage of successful trials. Test-retest reliability was evaluated with 3 different complementary approaches, i.e. a Bland-Altman analysis, an intraclass correlation coefficient (ICC) and a standard error of measurement (SEm). Thirty participants (24.6 years old; 17 males, 25 right-handed) completed both assessments. The mean discrimination thresholds were 7.0 ± 2.4 (mean ± standard deviation) and 5.9 ± 2.1 degrees for the first and the second assessment session, respectively. This small difference between assessments was significant (- 1.1 ± 2.2 degrees), however. The assessment protocol was characterized by a fair to good test-retest reliability (ICC = 0.47). This study demonstrated the potential of this assessment protocol to objectively quantify elbow position sense in healthy individuals. Futures studies will validate this protocol in older adults and in individuals who sustained a stroke.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 167 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 25 15%
Student > Bachelor 20 12%
Student > Ph. D. Student 17 10%
Researcher 16 10%
Professor 5 3%
Other 21 13%
Unknown 63 38%
Readers by discipline Count As %
Nursing and Health Professions 29 17%
Engineering 19 11%
Medicine and Dentistry 14 8%
Neuroscience 9 5%
Psychology 9 5%
Other 23 14%
Unknown 64 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 August 2019.
All research outputs
#13,347,438
of 23,028,364 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#628
of 1,293 outputs
Outputs of similar age
#167,650
of 333,153 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#15
of 29 outputs
Altmetric has tracked 23,028,364 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,293 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 gotten more attention than average, scoring higher than 50% 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 333,153 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.