Literature DB >> 26158005

Usability and performance-informed selection of personalized mental tasks for an online near-infrared spectroscopy brain-computer interface.

Sabine Weyand1, Larissa Schudlo1, Kaori Takehara-Nishiuchi2, Tom Chau1.   

Abstract

Brain-computer interfaces (BCIs) allow individuals to use only cognitive activities to interact with their environment. The widespread use of BCIs is limited, due in part to their lack of user-friendliness. The main goal of this work was to develop a more user-centered BCI and determine if: (1) individuals can acquire control of an online near-infrared spectroscopy BCI via usability and performance-informed selection of mental tasks without compromising classification accuracy and (2) the combination of usability and performance-informed selection of mental tasks yields subjective ease-of-use ratings that exceed those attainable with prescribed mental tasks. Twenty able-bodied participants were recruited. Half of the participants served as a control group, using the state-of-the-art prescribed mental strategies. The other half of the participants comprised the study group, choosing their own personalized mental strategies out of eleven possible tasks. It was concluded that users were, in fact, able to acquire control of the more user-centered BCI without a significant change in accuracy compared to the prescribed task BCI. Furthermore, the personalized BCI yielded higher subjective ease-of-use ratings than the prescribed BCI. Average online accuracies of [Formula: see text] and [Formula: see text] were achieved by the personalized and prescribed mental task groups, respectively.

Entities:  

Keywords:  brain-computer interface; ease-of-use; near-infrared spectroscopy; personalized mental tasks; user selected mental tasks; user-centered

Year:  2015        PMID: 26158005      PMCID: PMC4478988          DOI: 10.1117/1.NPh.2.2.025001

Source DB:  PubMed          Journal:  Neurophotonics        ISSN: 2329-423X            Impact factor:   3.593


  73 in total

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2.  Towards a system-paced near-infrared spectroscopy brain-computer interface: differentiating prefrontal activity due to mental arithmetic and mental singing from the no-control state.

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10.  Intersession consistency of single-trial classification of the prefrontal response to mental arithmetic and the no-control state by NIRS.

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  6 in total

1.  Correlates of Near-Infrared Spectroscopy Brain-Computer Interface Accuracy in a Multi-Class Personalization Framework.

Authors:  Sabine Weyand; Tom Chau
Journal:  Front Hum Neurosci       Date:  2015-09-30       Impact factor: 3.169

2.  Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain-computer interface: three-class classification of rest, right-, and left-hand motor execution.

Authors:  Thanawin Trakoolwilaiwan; Bahareh Behboodi; Jaeseok Lee; Kyungsoo Kim; Ji-Woong Choi
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Review 3.  A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives.

Authors:  Inchul Choi; Ilsun Rhiu; Yushin Lee; Myung Hwan Yun; Chang S Nam
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4.  See, Hear, or Feel - to Speak: A Versatile Multiple-Choice Functional Near-Infrared Spectroscopy-Brain-Computer Interface Feasible With Visual, Auditory, or Tactile Instructions.

Authors:  Laurien Nagels-Coune; Lars Riecke; Amaia Benitez-Andonegui; Simona Klinkhammer; Rainer Goebel; Peter De Weerd; Michael Lührs; Bettina Sorger
Journal:  Front Hum Neurosci       Date:  2021-11-25       Impact factor: 3.169

5.  A pediatric near-infrared spectroscopy brain-computer interface based on the detection of emotional valence.

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Journal:  Front Hum Neurosci       Date:  2022-09-23       Impact factor: 3.473

6.  An Augmented-Reality fNIRS-Based Brain-Computer Interface: A Proof-of-Concept Study.

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Journal:  Front Neurosci       Date:  2020-04-28       Impact factor: 4.677

  6 in total

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