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Performance assessment in brain-computer interface-based augmentative and alternative communication

Overview of attention for article published in BioMedical Engineering OnLine, May 2013
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

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3 patents
googleplus
1 Google+ user

Citations

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46 Dimensions

Readers on

mendeley
141 Mendeley
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1 CiteULike
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Title
Performance assessment in brain-computer interface-based augmentative and alternative communication
Published in
BioMedical Engineering OnLine, May 2013
DOI 10.1186/1475-925x-12-43
Pubmed ID
Authors

David E Thompson, Stefanie Blain-Moraes, Jane E Huggins

Abstract

A large number of incommensurable metrics are currently used to report the performance of brain-computer interfaces (BCI) used for augmentative and alterative communication (AAC). The lack of standard metrics precludes the comparison of different BCI-based AAC systems, hindering rapid growth and development of this technology. This paper presents a review of the metrics that have been used to report performance of BCIs used for AAC from January 2005 to January 2012. We distinguish between Level 1 metrics used to report performance at the output of the BCI Control Module, which translates brain signals into logical control output, and Level 2 metrics at the Selection Enhancement Module, which translates logical control to semantic control. We recommend that: (1) the commensurate metrics Mutual Information or Information Transfer Rate (ITR) be used to report Level 1 BCI performance, as these metrics represent information throughput, which is of interest in BCIs for AAC; 2) the BCI-Utility metric be used to report Level 2 BCI performance, as it is capable of handling all current methods of improving BCI performance; (3) these metrics should be supplemented by information specific to each unique BCI configuration; and (4) studies involving Selection Enhancement Modules should report performance at both Level 1 and Level 2 in the BCI system. Following these recommendations will enable efficient comparison between both BCI Control and Selection Enhancement Modules, accelerating research and development of BCI-based AAC systems.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 141 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
France 1 <1%
Italy 1 <1%
Germany 1 <1%
United Kingdom 1 <1%
Brazil 1 <1%
Belgium 1 <1%
Iran, Islamic Republic of 1 <1%
Unknown 129 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 22%
Student > Master 24 17%
Researcher 16 11%
Student > Bachelor 14 10%
Student > Doctoral Student 9 6%
Other 24 17%
Unknown 23 16%
Readers by discipline Count As %
Engineering 50 35%
Computer Science 21 15%
Neuroscience 9 6%
Agricultural and Biological Sciences 7 5%
Medicine and Dentistry 7 5%
Other 18 13%
Unknown 29 21%
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 21 June 2022.
All research outputs
#6,392,410
of 22,711,242 outputs
Outputs from BioMedical Engineering OnLine
#158
of 821 outputs
Outputs of similar age
#54,379
of 195,181 outputs
Outputs of similar age from BioMedical Engineering OnLine
#2
of 14 outputs
Altmetric has tracked 22,711,242 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 821 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 79% 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 195,181 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 70% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.