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KAPS (kinematic assessment of passive stretch): a tool to assess elbow flexor and extensor spasticity after stroke using a robotic exoskeleton

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, June 2017
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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1 X user
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1 Wikipedia page

Citations

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21 Dimensions

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121 Mendeley
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Title
KAPS (kinematic assessment of passive stretch): a tool to assess elbow flexor and extensor spasticity after stroke using a robotic exoskeleton
Published in
Journal of NeuroEngineering and Rehabilitation, June 2017
DOI 10.1186/s12984-017-0272-8
Pubmed ID
Authors

Andrew Centen, Catherine R. Lowrey, Stephen H. Scott, Ting-Ting Yeh, George Mochizuki

Abstract

Spasticity is a common sequela of stroke. Traditional assessment methods include relatively coarse scales that may not capture all characteristics of elevated muscle tone. Thus, the aim of this study was to develop a tool to quantitatively assess post-stroke spasticity in the upper extremity. Ninety-six healthy individuals and 46 individuals with stroke participated in this study. The kinematic assessment of passive stretch (KAPS) protocol consisted of passive elbow stretch in flexion and extension across an 80° range in 5 movement durations. Seven parameters were identified and assessed to characterize spasticity (peak velocity, final angle, creep (or release), between-arm peak velocity difference, between-arm final angle, between-arm creep, and between-arm catch angle). The fastest movement duration (600 ms) was most effective at identifying impairment in each parameter associated with spasticity. A decrease in peak velocity during passive stretch between the affected and unaffected limb was most effective at identifying individuals as impaired. Spasticity was also associated with a decreased passive range (final angle) and a classic 'catch and release' as seen through between-arm catch and creep metrics. The KAPS protocol and robotic technology can provide a sensitive and quantitative assessment of post-stroke elbow spasticity not currently attainable through traditional measures.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 121 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 12%
Student > Master 13 11%
Student > Bachelor 10 8%
Researcher 9 7%
Other 9 7%
Other 18 15%
Unknown 48 40%
Readers by discipline Count As %
Engineering 19 16%
Nursing and Health Professions 14 12%
Medicine and Dentistry 13 11%
Neuroscience 8 7%
Sports and Recreations 2 2%
Other 9 7%
Unknown 56 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 14 September 2022.
All research outputs
#6,595,160
of 23,330,477 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#405
of 1,305 outputs
Outputs of similar age
#104,931
of 317,502 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#5
of 23 outputs
Altmetric has tracked 23,330,477 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1,305 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has gotten more attention than average, scoring higher than 68% 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 317,502 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
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 has done well, scoring higher than 78% of its contemporaries.