Investigating Mental Task Combination for Brain-Computer Interface Based on Brain State Discrimination Using Subjective Ratings Article Swipe
Akira Masuo
,
Takuto Sakuma
,
Shōhei Kato
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.14326/abe.12.129
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.14326/abe.12.129
Brain-computer interface (BCI) has attracted attention as a means of assisting patients with intractable neurological diseases to communicate their intentions. However, there are no reports examining the mental tasks that are effective in acquiring physiological signals for BCI, based on evaluation of classification performance and subjective usability of the mental tasks. This study aimed to investigate preferable mental task combinations that could be utilized in the task selection process for near-infrared spectroscopy (NIRS)-based BCIs. We evaluated the classification model performance of brain activation responses using NIRS signals and subjective usability of mental tasks. NIRS signals were measured in 10 healthy adult participants while they performed mental arithmetic task (MA), mental singing task (MS), mental writing task (MW), and mental figure rotation task (MFR), using a block design consisting of a 30-s rest and 30-s task period. For six combinations of mental tasks, binary classification models were constructed using random forest with a dimension reduction method, and the classification performance was evaluated using three-fold cross-validation. We also measured the subjective usability of the mental tasks. The results showed that MW vs. MFR was classified with an average accuracy of 71.5%, and six participants achieved over 70% accuracy. The subjective ratings of state anxiety and acceptability showed that all the mental tasks were rated as acceptable for use in BCI applications. These findings may be utilized as the preliminary communication tasks in the process of selecting appropriate cognitive tasks for BCI for individual users.
Related Topics
Concepts
Brain–computer interface
Usability
Task (project management)
Computer science
Cognition
Brain activity and meditation
Psychology
Interface (matter)
Cognitive psychology
Electroencephalography
Human–computer interaction
Parallel computing
Psychiatry
Maximum bubble pressure method
Neuroscience
Economics
Bubble
Management
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.14326/abe.12.129
- https://www.jstage.jst.go.jp/article/abe/12/0/12_12_129/_pdf
- OA Status
- gold
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4376602179
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4376602179Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.14326/abe.12.129Digital Object Identifier
- Title
-
Investigating Mental Task Combination for Brain-Computer Interface Based on Brain State Discrimination Using Subjective RatingsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-01Full publication date if available
- Authors
-
Akira Masuo, Takuto Sakuma, Shōhei KatoList of authors in order
- Landing page
-
https://doi.org/10.14326/abe.12.129Publisher landing page
- PDF URL
-
https://www.jstage.jst.go.jp/article/abe/12/0/12_12_129/_pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.jstage.jst.go.jp/article/abe/12/0/12_12_129/_pdfDirect OA link when available
- Concepts
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Brain–computer interface, Usability, Task (project management), Computer science, Cognition, Brain activity and meditation, Psychology, Interface (matter), Cognitive psychology, Electroencephalography, Human–computer interaction, Parallel computing, Psychiatry, Maximum bubble pressure method, Neuroscience, Economics, Bubble, ManagementTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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24Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.are | 22, 30 |
| abstract_inverted_index.for | 36, 69, 214, 237, 239 |
| abstract_inverted_index.has | 3 |
| abstract_inverted_index.may | 221 |
| abstract_inverted_index.six | 137, 190 |
| abstract_inverted_index.the | 26, 48, 65, 76, 156, 167, 171, 207, 225, 230 |
| abstract_inverted_index.use | 215 |
| abstract_inverted_index.vs. | 179 |
| abstract_inverted_index.was | 159, 181 |
| abstract_inverted_index.30-s | 130, 133 |
| abstract_inverted_index.BCI, | 37 |
| abstract_inverted_index.NIRS | 85, 93 |
| abstract_inverted_index.This | 51 |
| abstract_inverted_index.also | 165 |
| abstract_inverted_index.over | 193 |
| abstract_inverted_index.rest | 131 |
| abstract_inverted_index.task | 58, 66, 107, 111, 115, 121, 134 |
| abstract_inverted_index.that | 29, 60, 177, 205 |
| abstract_inverted_index.they | 103 |
| abstract_inverted_index.were | 95, 145, 210 |
| abstract_inverted_index.with | 12, 150, 183 |
| abstract_inverted_index.(BCI) | 2 |
| abstract_inverted_index.(MA), | 108 |
| abstract_inverted_index.(MS), | 112 |
| abstract_inverted_index.(MW), | 116 |
| abstract_inverted_index.BCIs. | 73 |
| abstract_inverted_index.These | 219 |
| abstract_inverted_index.adult | 100 |
| abstract_inverted_index.aimed | 53 |
| abstract_inverted_index.based | 38 |
| abstract_inverted_index.block | 125 |
| abstract_inverted_index.brain | 81 |
| abstract_inverted_index.could | 61 |
| abstract_inverted_index.means | 8 |
| abstract_inverted_index.model | 78 |
| abstract_inverted_index.rated | 211 |
| abstract_inverted_index.state | 200 |
| abstract_inverted_index.study | 52 |
| abstract_inverted_index.tasks | 28, 209, 228, 236 |
| abstract_inverted_index.their | 18 |
| abstract_inverted_index.there | 21 |
| abstract_inverted_index.using | 84, 123, 147, 161 |
| abstract_inverted_index.while | 102 |
| abstract_inverted_index.(MFR), | 122 |
| abstract_inverted_index.71.5%, | 188 |
| abstract_inverted_index.binary | 142 |
| abstract_inverted_index.design | 126 |
| abstract_inverted_index.figure | 119 |
| abstract_inverted_index.forest | 149 |
| abstract_inverted_index.mental | 27, 49, 57, 91, 105, 109, 113, 118, 140, 172, 208 |
| abstract_inverted_index.models | 144 |
| abstract_inverted_index.random | 148 |
| abstract_inverted_index.showed | 176, 204 |
| abstract_inverted_index.tasks, | 141 |
| abstract_inverted_index.tasks. | 50, 92, 173 |
| abstract_inverted_index.users. | 241 |
| abstract_inverted_index.anxiety | 201 |
| abstract_inverted_index.average | 185 |
| abstract_inverted_index.healthy | 99 |
| abstract_inverted_index.method, | 154 |
| abstract_inverted_index.period. | 135 |
| abstract_inverted_index.process | 68, 231 |
| abstract_inverted_index.ratings | 198 |
| abstract_inverted_index.reports | 24 |
| abstract_inverted_index.results | 175 |
| abstract_inverted_index.signals | 35, 86, 94 |
| abstract_inverted_index.singing | 110 |
| abstract_inverted_index.writing | 114 |
| abstract_inverted_index.However, | 20 |
| abstract_inverted_index.accuracy | 186 |
| abstract_inverted_index.achieved | 192 |
| abstract_inverted_index.diseases | 15 |
| abstract_inverted_index.findings | 220 |
| abstract_inverted_index.measured | 96, 166 |
| abstract_inverted_index.patients | 11 |
| abstract_inverted_index.rotation | 120 |
| abstract_inverted_index.utilized | 63, 223 |
| abstract_inverted_index.accuracy. | 195 |
| abstract_inverted_index.acquiring | 33 |
| abstract_inverted_index.assisting | 10 |
| abstract_inverted_index.attention | 5 |
| abstract_inverted_index.attracted | 4 |
| abstract_inverted_index.cognitive | 235 |
| abstract_inverted_index.dimension | 152 |
| abstract_inverted_index.effective | 31 |
| abstract_inverted_index.evaluated | 75, 160 |
| abstract_inverted_index.examining | 25 |
| abstract_inverted_index.interface | 1 |
| abstract_inverted_index.performed | 104 |
| abstract_inverted_index.reduction | 153 |
| abstract_inverted_index.responses | 83 |
| abstract_inverted_index.selecting | 233 |
| abstract_inverted_index.selection | 67 |
| abstract_inverted_index.usability | 46, 89, 169 |
| abstract_inverted_index.acceptable | 213 |
| abstract_inverted_index.activation | 82 |
| abstract_inverted_index.arithmetic | 106 |
| abstract_inverted_index.classified | 182 |
| abstract_inverted_index.consisting | 127 |
| abstract_inverted_index.evaluation | 40 |
| abstract_inverted_index.individual | 240 |
| abstract_inverted_index.preferable | 56 |
| abstract_inverted_index.subjective | 45, 88, 168, 197 |
| abstract_inverted_index.three-fold | 162 |
| abstract_inverted_index.appropriate | 234 |
| abstract_inverted_index.communicate | 17 |
| abstract_inverted_index.constructed | 146 |
| abstract_inverted_index.intentions. | 19 |
| abstract_inverted_index.intractable | 13 |
| abstract_inverted_index.investigate | 55 |
| abstract_inverted_index.performance | 43, 79, 158 |
| abstract_inverted_index.preliminary | 226 |
| abstract_inverted_index.(NIRS)-based | 72 |
| abstract_inverted_index.combinations | 59, 138 |
| abstract_inverted_index.neurological | 14 |
| abstract_inverted_index.participants | 101, 191 |
| abstract_inverted_index.spectroscopy | 71 |
| abstract_inverted_index.acceptability | 203 |
| abstract_inverted_index.applications. | 218 |
| abstract_inverted_index.communication | 227 |
| abstract_inverted_index.near-infrared | 70 |
| abstract_inverted_index.physiological | 34 |
| abstract_inverted_index.Brain-computer | 0 |
| abstract_inverted_index.classification | 42, 77, 143, 157 |
| abstract_inverted_index.cross-validation. | 163 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.06741024 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |