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A review of wearable sensors and systems with application in rehabilitation

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, January 2012
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

policy
1 policy source
twitter
5 tweeters
patent
8 patents
facebook
2 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
1206 Dimensions

Readers on

mendeley
2401 Mendeley
citeulike
2 CiteULike
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Title
A review of wearable sensors and systems with application in rehabilitation
Published in
Journal of NeuroEngineering and Rehabilitation, January 2012
DOI 10.1186/1743-0003-9-21
Pubmed ID
Authors

Shyamal Patel, Hyung Park, Paolo Bonato, Leighton Chan, Mary Rodgers

Abstract

The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 2,401 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 28 1%
United Kingdom 14 <1%
Germany 11 <1%
Italy 9 <1%
Spain 8 <1%
India 6 <1%
Portugal 4 <1%
Malaysia 4 <1%
France 4 <1%
Other 44 2%
Unknown 2269 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 593 25%
Student > Master 476 20%
Researcher 337 14%
Student > Bachelor 246 10%
Student > Doctoral Student 125 5%
Other 401 17%
Unknown 223 9%
Readers by discipline Count As %
Engineering 861 36%
Computer Science 392 16%
Medicine and Dentistry 165 7%
Materials Science 84 3%
Nursing and Health Professions 69 3%
Other 501 21%
Unknown 329 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 10 September 2020.
All research outputs
#1,440,804
of 17,888,394 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#61
of 1,115 outputs
Outputs of similar age
#9,527
of 134,039 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#1
of 6 outputs
Altmetric has tracked 17,888,394 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,115 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has done particularly well, scoring higher than 94% 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 134,039 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them