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Robotic and Virtual Reality BCIs Using Spatial Tactile and Auditory Oddball Paradigms

Overview of attention for article published in Frontiers in Neurorobotics, December 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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Title
Robotic and Virtual Reality BCIs Using Spatial Tactile and Auditory Oddball Paradigms
Published in
Frontiers in Neurorobotics, December 2016
DOI 10.3389/fnbot.2016.00020
Pubmed ID
Authors

Tomasz M. Rutkowski

Abstract

The paper reviews nine robotic and virtual reality (VR) brain-computer interface (BCI) projects developed by the author, in collaboration with his graduate students, within the BCI-lab research group during its association with University of Tsukuba, Japan. The nine novel approaches are discussed in applications to direct brain-robot and brain-virtual-reality-agent control interfaces using tactile and auditory BCI technologies. The BCI user intentions are decoded from the brainwaves in realtime using a non-invasive electroencephalography (EEG) and they are translated to a symbiotic robot or virtual reality agent thought-based only control. A communication protocol between the BCI output and the robot or the virtual environment is realized in a symbiotic communication scenario using an user datagram protocol (UDP), which constitutes an internet of things (IoT) control scenario. Results obtained from healthy users reproducing simple brain-robot and brain-virtual-agent control tasks in online experiments support the research goal of a possibility to interact with robotic devices and virtual reality agents using symbiotic thought-based BCI technologies. An offline BCI classification accuracy boosting method, using a previously proposed information geometry derived approach, is also discussed in order to further support the reviewed robotic and virtual reality thought-based control paradigms.

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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 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Germany 1 1%
Unknown 96 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 22%
Student > Ph. D. Student 22 22%
Researcher 10 10%
Student > Bachelor 9 9%
Student > Doctoral Student 7 7%
Other 10 10%
Unknown 18 18%
Readers by discipline Count As %
Computer Science 21 21%
Engineering 17 17%
Neuroscience 13 13%
Psychology 9 9%
Agricultural and Biological Sciences 3 3%
Other 14 14%
Unknown 21 21%
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 18 November 2018.
All research outputs
#3,808,797
of 23,577,761 outputs
Outputs from Frontiers in Neurorobotics
#80
of 918 outputs
Outputs of similar age
#73,080
of 423,116 outputs
Outputs of similar age from Frontiers in Neurorobotics
#1
of 9 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 918 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 91% 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 423,116 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 82% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them