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Development of an electrooculogram-based eye-computer interface for communication of individuals with amyotrophic lateral sclerosis

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, September 2017
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Average Attention Score compared to outputs of the same age and source

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3 X users
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1 Facebook page
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1 Google+ user

Citations

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27 Dimensions

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87 Mendeley
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Title
Development of an electrooculogram-based eye-computer interface for communication of individuals with amyotrophic lateral sclerosis
Published in
Journal of NeuroEngineering and Rehabilitation, September 2017
DOI 10.1186/s12984-017-0303-5
Pubmed ID
Authors

Won-Du Chang, Ho-Seung Cha, Do Yeon Kim, Seung Hyun Kim, Chang-Hwan Im

Abstract

Electrooculogram (EOG) can be used to continuously track eye movements and can thus be considered as an alternative to conventional camera-based eye trackers. Although many EOG-based eye tracking systems have been studied with the ultimate goal of providing a new way of communication for individuals with amyotrophic lateral sclerosis (ALS), most of them were tested with healthy people only. In this paper, we investigated the feasibility of EOG-based eye-writing as a new mode of communication for individuals with ALS. We developed an EOG-based eye-writing system and tested this system with 18 healthy participants and three participants with ALS. We also applied a new method for removing crosstalk between horizontal and vertical EOG components. All study participants were asked to eye-write specially designed patterns of 10 Arabic numbers three times after a short practice session. Our system achieved a mean recognition rates of 95.93% for healthy participants and showed recognition rates of 95.00%, 66.67%, and 93.33% for the three participants with ALS. The low recognition rates in one of the participants with ALS was mainly due to miswritten letters, the number of which decreased as the experiment proceeded. Our proposed eye-writing system is a feasible human-computer interface (HCI) tool for enabling practical communication of individuals with ALS.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 87 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 13 15%
Student > Master 9 10%
Student > Ph. D. Student 6 7%
Researcher 5 6%
Lecturer 5 6%
Other 10 11%
Unknown 39 45%
Readers by discipline Count As %
Engineering 22 25%
Nursing and Health Professions 7 8%
Medicine and Dentistry 7 8%
Neuroscience 3 3%
Computer Science 2 2%
Other 7 8%
Unknown 39 45%
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 10 April 2018.
All research outputs
#12,761,723
of 23,003,906 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#557
of 1,290 outputs
Outputs of similar age
#143,884
of 316,069 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#14
of 25 outputs
Altmetric has tracked 23,003,906 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,290 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 55% 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 316,069 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 53% of its contemporaries.
We're also able to compare this research output to 25 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.