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An exploration of spatial auditory BCI paradigms with different sounds: music notes versus beeps

Overview of attention for article published in Cognitive Neurodynamics, January 2016
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Title
An exploration of spatial auditory BCI paradigms with different sounds: music notes versus beeps
Published in
Cognitive Neurodynamics, January 2016
DOI 10.1007/s11571-016-9377-1
Pubmed ID
Authors

Minqiang Huang, Ian Daly, Jing Jin, Yu Zhang, Xingyu Wang, Andrzej Cichocki

Abstract

Visual brain-computer interfaces (BCIs) are not suitable for people who cannot reliably maintain their eye gaze. Considering that this group usually maintains audition, an auditory based BCI may be a good choice for them. In this paper, we explore two auditory patterns: (1) a pattern utilizing symmetrical spatial cues with multiple frequency beeps [called the high low medium (HLM) pattern], and (2) a pattern utilizing non-symmetrical spatial cues with six tones derived from the diatonic scale [called the diatonic scale (DS) pattern]. These two patterns are compared to each other in terms of accuracy to determine which auditory pattern is better. The HLM pattern uses three different frequency beeps and has a symmetrical spatial distribution. The DS pattern uses six spoken stimuli, which are six notes solmizated as "do", "re", "mi", "fa", "sol" and "la", and derived from the diatonic scale. These six sounds are distributed to six, spatially distributed, speakers. Thus, we compare a BCI paradigm using beeps with another BCI paradigm using tones on the diatonic scale, when the stimuli are spatially distributed. Although no significant differences are found between the ERPs, the HLM pattern performs better than the DS pattern: the online accuracy achieved with the HLM pattern is significantly higher than that achieved with the DS pattern (p = 0.0028).

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Korea, Republic of 1 2%
Austria 1 2%
Unknown 43 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 22%
Student > Master 9 20%
Researcher 4 9%
Student > Doctoral Student 2 4%
Other 2 4%
Other 7 15%
Unknown 12 26%
Readers by discipline Count As %
Engineering 8 17%
Computer Science 7 15%
Neuroscience 6 13%
Psychology 5 11%
Arts and Humanities 3 7%
Other 4 9%
Unknown 13 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 June 2016.
All research outputs
#13,978,999
of 22,870,727 outputs
Outputs from Cognitive Neurodynamics
#95
of 319 outputs
Outputs of similar age
#200,824
of 395,807 outputs
Outputs of similar age from Cognitive Neurodynamics
#2
of 11 outputs
Altmetric has tracked 22,870,727 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 319 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 68% 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 395,807 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
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.