↓ Skip to main content

Combining Brain–Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges

Overview of attention for article published in Frontiers in Neuroscience, January 2010
Altmetric Badge

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 (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
12 X users

Citations

dimensions_citation
652 Dimensions

Readers on

mendeley
885 Mendeley
citeulike
3 CiteULike
connotea
1 Connotea
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Combining Brain–Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges
Published in
Frontiers in Neuroscience, January 2010
DOI 10.3389/fnins.2010.00161
Pubmed ID
Authors

J. d. R. Millán, R. Rupp, G. R. Müller-Putz, R. Murray-Smith, C. Giugliemma, M. Tangermann, C. Vidaurre, F. Cincotti, A. Kübler, R. Leeb, C. Neuper, K.-R. Müller, D. Mattia

Abstract

In recent years, new research has brought the field of electroencephalogram (EEG)-based brain-computer interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely, "Communication and Control", "Motor Substitution", "Entertainment", and "Motor Recovery". We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users' mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 885 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 1%
Germany 11 1%
Switzerland 4 <1%
Netherlands 4 <1%
United Kingdom 4 <1%
Brazil 4 <1%
Austria 3 <1%
Italy 3 <1%
Spain 3 <1%
Other 27 3%
Unknown 810 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 190 21%
Student > Master 154 17%
Researcher 141 16%
Student > Bachelor 100 11%
Student > Doctoral Student 41 5%
Other 131 15%
Unknown 128 14%
Readers by discipline Count As %
Engineering 306 35%
Computer Science 120 14%
Neuroscience 83 9%
Agricultural and Biological Sciences 54 6%
Medicine and Dentistry 39 4%
Other 118 13%
Unknown 165 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 February 2019.
All research outputs
#4,601,871
of 25,373,627 outputs
Outputs from Frontiers in Neuroscience
#3,564
of 11,538 outputs
Outputs of similar age
#25,071
of 172,626 outputs
Outputs of similar age from Frontiers in Neuroscience
#10
of 37 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,538 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has gotten more attention than average, scoring higher than 69% 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 172,626 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.