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Exergaming for balance training of elderly: state of the art and future developments

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, September 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#42 of 1,413)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

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2 news outlets
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14 X users
patent
1 patent

Citations

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207 Dimensions

Readers on

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558 Mendeley
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Title
Exergaming for balance training of elderly: state of the art and future developments
Published in
Journal of NeuroEngineering and Rehabilitation, September 2013
DOI 10.1186/1743-0003-10-101
Pubmed ID
Authors

Mike van Diest, Claudine JC Lamoth, Jan Stegenga, Gijsbertus J Verkerke, Klaas Postema

Abstract

Fall injuries are responsible for physical dysfunction, significant disability, and loss of independence among elderly. Poor postural control is one of the major risk factors for falling but can be trained in fall prevention programs. These however suffer from low therapy adherence, particularly if prevention is the goal. To provide a fun and motivating training environment for elderly, exercise games, or exergames, have been studied as balance training tools in the past years. The present paper reviews the effects of exergame training programs on postural control of elderly reported so far. Additionally we aim to provide an in-depth discussion of technologies and outcome measures utilized in exergame studies. Thirteen papers were included in the analysis. Most of the reviewed studies reported positive results with respect to improvements in balance ability after a training period, yet few reached significant levels. Outcome measures for quantification of postural control are under continuous dispute and no gold standard is present. Clinical measures used in the studies reviewed are well validated yet only give a global indication of balance ability. Instrumented measures were unable to detect small changes in balance ability as they are mainly based on calculating summary statistics, thereby ignoring the time-varying structure of the signals. Both methods only allow for measuring balance after the exergame intervention program. Current developments in sensor technology allow for accurate registration of movements and rapid analysis of signals. We propose to quantify the time-varying structure of postural control during gameplay using low-cost sensor systems. Continuous monitoring of balance ability leaves the user unaware of the measurements and allows for generating user-specific exergame training programs and feedback, both during one game and in timeframes of weeks or months. This approach is unique and unlocks the as of yet untapped potential of exergames as balance training tools for community dwelling elderly.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users 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 558 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 3 <1%
Italy 3 <1%
France 2 <1%
Mexico 2 <1%
Canada 2 <1%
Australia 2 <1%
Chile 1 <1%
Norway 1 <1%
Brazil 1 <1%
Other 5 <1%
Unknown 536 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 109 20%
Student > Bachelor 97 17%
Student > Ph. D. Student 92 16%
Researcher 44 8%
Student > Doctoral Student 25 4%
Other 86 15%
Unknown 105 19%
Readers by discipline Count As %
Medicine and Dentistry 82 15%
Nursing and Health Professions 67 12%
Engineering 62 11%
Sports and Recreations 57 10%
Computer Science 51 9%
Other 111 20%
Unknown 128 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 2018.
All research outputs
#1,379,904
of 25,371,288 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#42
of 1,413 outputs
Outputs of similar age
#12,307
of 215,505 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#2
of 11 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,413 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done particularly well, scoring higher than 97% 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 215,505 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 94% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.