Using Statistical Properties and Random Forests, Classification Performance Model Evaluation for the Mental Arithmetic Task-Brain Computer Interface Article Swipe
A.Nirmala devi
,
R. Vidhya
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.13052/rp-9788770040723.016
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.13052/rp-9788770040723.016
Ourobjective is to find an efficient method to classify the subject's mental cognitive workload as good or bad by obtaining features that can describe the continuous and underlying temporal dynamics of electroencephalography (EEG) data during the performance of mental tasks. To develop a BCI model that can forecast mental states like good and bad, we explore the ensemble learning technique using classifiers like the random forest classifier. From the alpha, beta, and gamma bands of EEG, the features like mean, root mean square, skewness, mode, data range, interquartile range (IQR), and three Hjorth parameters are extracted to differentiate a signal before-during mental arithmetic task. Our suggested model's analysis and results demonstrate that, when applying these techniques, accuracy is 96%. This model is further utilized for the application of automation in the Internet of Things (IoT).
Related Topics
Concepts
Computer science
Mental arithmetic
Task (project management)
Interface (matter)
Brain–computer interface
Random forest
Arithmetic
Artificial intelligence
Parallel computing
Mathematics
Electroencephalography
Psychology
Medicine
Psychiatry
Economics
Bubble
Heart rate
Radiology
Blood pressure
Management
Maximum bubble pressure method
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.13052/rp-9788770040723.016
- https://www.riverpublishers.com/pdf/ebook/chapter/RP_9788770040723C16.pdf
- OA Status
- gold
- References
- 14
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386704144
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4386704144Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.13052/rp-9788770040723.016Digital Object Identifier
- Title
-
Using Statistical Properties and Random Forests, Classification Performance Model Evaluation for the Mental Arithmetic Task-Brain Computer InterfaceWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-01Full publication date if available
- Authors
-
A.Nirmala devi, R. VidhyaList of authors in order
- Landing page
-
https://doi.org/10.13052/rp-9788770040723.016Publisher landing page
- PDF URL
-
https://www.riverpublishers.com/pdf/ebook/chapter/RP_9788770040723C16.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.riverpublishers.com/pdf/ebook/chapter/RP_9788770040723C16.pdfDirect OA link when available
- Concepts
-
Computer science, Mental arithmetic, Task (project management), Interface (matter), Brain–computer interface, Random forest, Arithmetic, Artificial intelligence, Parallel computing, Mathematics, Electroencephalography, Psychology, Medicine, Psychiatry, Economics, Bubble, Heart rate, Radiology, Blood pressure, Management, Maximum bubble pressure methodTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
14Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4386704144 |
|---|---|
| doi | https://doi.org/10.13052/rp-9788770040723.016 |
| ids.doi | https://doi.org/10.13052/rp-9788770040723.016 |
| ids.openalex | https://openalex.org/W4386704144 |
| fwci | 0.0 |
| type | article |
| title | Using Statistical Properties and Random Forests, Classification Performance Model Evaluation for the Mental Arithmetic Task-Brain Computer Interface |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | 85 |
| biblio.first_page | 81 |
| topics[0].id | https://openalex.org/T10320 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.8780999779701233 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Neural Networks and Applications |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.7157933115959167 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C2992503517 |
| concepts[1].level | 4 |
| concepts[1].score | 0.6846730709075928 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q620584 |
| concepts[1].display_name | Mental arithmetic |
| concepts[2].id | https://openalex.org/C2780451532 |
| concepts[2].level | 2 |
| concepts[2].score | 0.6838711500167847 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q759676 |
| concepts[2].display_name | Task (project management) |
| concepts[3].id | https://openalex.org/C113843644 |
| concepts[3].level | 4 |
| concepts[3].score | 0.6230310797691345 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q901882 |
| concepts[3].display_name | Interface (matter) |
| concepts[4].id | https://openalex.org/C173201364 |
| concepts[4].level | 3 |
| concepts[4].score | 0.6214951276779175 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q897410 |
| concepts[4].display_name | Brain–computer interface |
| concepts[5].id | https://openalex.org/C169258074 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5833197236061096 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q245748 |
| concepts[5].display_name | Random forest |
| concepts[6].id | https://openalex.org/C94375191 |
| concepts[6].level | 1 |
| concepts[6].score | 0.46699610352516174 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11205 |
| concepts[6].display_name | Arithmetic |
| concepts[7].id | https://openalex.org/C154945302 |
| concepts[7].level | 1 |
| concepts[7].score | 0.34700554609298706 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[7].display_name | Artificial intelligence |
| concepts[8].id | https://openalex.org/C173608175 |
| concepts[8].level | 1 |
| concepts[8].score | 0.25777238607406616 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q232661 |
| concepts[8].display_name | Parallel computing |
| concepts[9].id | https://openalex.org/C33923547 |
| concepts[9].level | 0 |
| concepts[9].score | 0.18267670273780823 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[9].display_name | Mathematics |
| concepts[10].id | https://openalex.org/C522805319 |
| concepts[10].level | 2 |
| concepts[10].score | 0.16459748148918152 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q179965 |
| concepts[10].display_name | Electroencephalography |
| concepts[11].id | https://openalex.org/C15744967 |
| concepts[11].level | 0 |
| concepts[11].score | 0.12599319219589233 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[11].display_name | Psychology |
| concepts[12].id | https://openalex.org/C71924100 |
| concepts[12].level | 0 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[12].display_name | Medicine |
| concepts[13].id | https://openalex.org/C118552586 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q7867 |
| concepts[13].display_name | Psychiatry |
| concepts[14].id | https://openalex.org/C162324750 |
| concepts[14].level | 0 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[14].display_name | Economics |
| concepts[15].id | https://openalex.org/C157915830 |
| concepts[15].level | 2 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q2928001 |
| concepts[15].display_name | Bubble |
| concepts[16].id | https://openalex.org/C2777953023 |
| concepts[16].level | 3 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q1073121 |
| concepts[16].display_name | Heart rate |
| concepts[17].id | https://openalex.org/C126838900 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q77604 |
| concepts[17].display_name | Radiology |
| concepts[18].id | https://openalex.org/C84393581 |
| concepts[18].level | 2 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q82642 |
| concepts[18].display_name | Blood pressure |
| concepts[19].id | https://openalex.org/C187736073 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q2920921 |
| concepts[19].display_name | Management |
| concepts[20].id | https://openalex.org/C129307140 |
| concepts[20].level | 3 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q6795880 |
| concepts[20].display_name | Maximum bubble pressure method |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.7157933115959167 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/mental-arithmetic |
| keywords[1].score | 0.6846730709075928 |
| keywords[1].display_name | Mental arithmetic |
| keywords[2].id | https://openalex.org/keywords/task |
| keywords[2].score | 0.6838711500167847 |
| keywords[2].display_name | Task (project management) |
| keywords[3].id | https://openalex.org/keywords/interface |
| keywords[3].score | 0.6230310797691345 |
| keywords[3].display_name | Interface (matter) |
| keywords[4].id | https://openalex.org/keywords/brain–computer-interface |
| keywords[4].score | 0.6214951276779175 |
| keywords[4].display_name | Brain–computer interface |
| keywords[5].id | https://openalex.org/keywords/random-forest |
| keywords[5].score | 0.5833197236061096 |
| keywords[5].display_name | Random forest |
| keywords[6].id | https://openalex.org/keywords/arithmetic |
| keywords[6].score | 0.46699610352516174 |
| keywords[6].display_name | Arithmetic |
| keywords[7].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[7].score | 0.34700554609298706 |
| keywords[7].display_name | Artificial intelligence |
| keywords[8].id | https://openalex.org/keywords/parallel-computing |
| keywords[8].score | 0.25777238607406616 |
| keywords[8].display_name | Parallel computing |
| keywords[9].id | https://openalex.org/keywords/mathematics |
| keywords[9].score | 0.18267670273780823 |
| keywords[9].display_name | Mathematics |
| keywords[10].id | https://openalex.org/keywords/electroencephalography |
| keywords[10].score | 0.16459748148918152 |
| keywords[10].display_name | Electroencephalography |
| keywords[11].id | https://openalex.org/keywords/psychology |
| keywords[11].score | 0.12599319219589233 |
| keywords[11].display_name | Psychology |
| language | en |
| locations[0].id | doi:10.13052/rp-9788770040723.016 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | |
| locations[0].pdf_url | https://www.riverpublishers.com/pdf/ebook/chapter/RP_9788770040723C16.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | proceedings-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Recent Trends in Data Science and its Applications |
| locations[0].landing_page_url | https://doi.org/10.13052/rp-9788770040723.016 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5111039367 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | A.Nirmala devi |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I145286018 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Computer Science and Engineering SRM Institute of Science and Technology Katankalathur, Chennai |
| authorships[0].institutions[0].id | https://openalex.org/I145286018 |
| authorships[0].institutions[0].ror | https://ror.org/050113w36 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I145286018 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | SRM Institute of Science and Technology |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | A.Nirmala devi |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Computer Science and Engineering SRM Institute of Science and Technology Katankalathur, Chennai |
| authorships[1].author.id | https://openalex.org/A5087524850 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | R. Vidhya |
| authorships[1].countries | IN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I145286018 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Computing Technologies SRM Institute of Science and Technology Katankulathur, India |
| authorships[1].institutions[0].id | https://openalex.org/I145286018 |
| authorships[1].institutions[0].ror | https://ror.org/050113w36 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I145286018 |
| authorships[1].institutions[0].country_code | IN |
| authorships[1].institutions[0].display_name | SRM Institute of Science and Technology |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | R. Vidhya |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | Department of Computing Technologies SRM Institute of Science and Technology Katankulathur, India |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.riverpublishers.com/pdf/ebook/chapter/RP_9788770040723C16.pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Using Statistical Properties and Random Forests, Classification Performance Model Evaluation for the Mental Arithmetic Task-Brain Computer Interface |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10320 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.8780999779701233 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Neural Networks and Applications |
| related_works | https://openalex.org/W2015326241, https://openalex.org/W2071129935, https://openalex.org/W2390569096, https://openalex.org/W2917517086, https://openalex.org/W2592357088, https://openalex.org/W2393285213, https://openalex.org/W3109411782, https://openalex.org/W2296761738, https://openalex.org/W2395744976, https://openalex.org/W2020763674 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.13052/rp-9788770040723.016 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://www.riverpublishers.com/pdf/ebook/chapter/RP_9788770040723C16.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | proceedings-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Recent Trends in Data Science and its Applications |
| best_oa_location.landing_page_url | https://doi.org/10.13052/rp-9788770040723.016 |
| primary_location.id | doi:10.13052/rp-9788770040723.016 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | |
| primary_location.pdf_url | https://www.riverpublishers.com/pdf/ebook/chapter/RP_9788770040723C16.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | proceedings-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Recent Trends in Data Science and its Applications |
| primary_location.landing_page_url | https://doi.org/10.13052/rp-9788770040723.016 |
| publication_date | 2023-01-01 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W2107104096, https://openalex.org/W2107549039, https://openalex.org/W2811235198, https://openalex.org/W2122149860, https://openalex.org/W2910134385, https://openalex.org/W4309552786, https://openalex.org/W2021589706, https://openalex.org/W4313443379, https://openalex.org/W3082045506, https://openalex.org/W2025210939, https://openalex.org/W4205997715, https://openalex.org/W4285251589, https://openalex.org/W3203139718, https://openalex.org/W2081895431 |
| referenced_works_count | 14 |
| abstract_inverted_index.a | 42, 98 |
| abstract_inverted_index.To | 40 |
| abstract_inverted_index.an | 4 |
| abstract_inverted_index.as | 14 |
| abstract_inverted_index.by | 18 |
| abstract_inverted_index.in | 129 |
| abstract_inverted_index.is | 1, 117, 121 |
| abstract_inverted_index.of | 30, 37, 74, 127, 132 |
| abstract_inverted_index.or | 16 |
| abstract_inverted_index.to | 2, 7, 96 |
| abstract_inverted_index.we | 54 |
| abstract_inverted_index.BCI | 43 |
| abstract_inverted_index.Our | 104 |
| abstract_inverted_index.and | 26, 52, 71, 90, 108 |
| abstract_inverted_index.are | 94 |
| abstract_inverted_index.bad | 17 |
| abstract_inverted_index.can | 22, 46 |
| abstract_inverted_index.for | 124 |
| abstract_inverted_index.the | 9, 24, 35, 56, 63, 68, 76, 125, 130 |
| abstract_inverted_index.96%. | 118 |
| abstract_inverted_index.EEG, | 75 |
| abstract_inverted_index.From | 67 |
| abstract_inverted_index.This | 119 |
| abstract_inverted_index.bad, | 53 |
| abstract_inverted_index.data | 33, 85 |
| abstract_inverted_index.find | 3 |
| abstract_inverted_index.good | 15, 51 |
| abstract_inverted_index.like | 50, 62, 78 |
| abstract_inverted_index.mean | 81 |
| abstract_inverted_index.root | 80 |
| abstract_inverted_index.that | 21, 45 |
| abstract_inverted_index.when | 112 |
| abstract_inverted_index.(EEG) | 32 |
| abstract_inverted_index.bands | 73 |
| abstract_inverted_index.beta, | 70 |
| abstract_inverted_index.gamma | 72 |
| abstract_inverted_index.mean, | 79 |
| abstract_inverted_index.mode, | 84 |
| abstract_inverted_index.model | 44, 120 |
| abstract_inverted_index.range | 88 |
| abstract_inverted_index.task. | 103 |
| abstract_inverted_index.that, | 111 |
| abstract_inverted_index.these | 114 |
| abstract_inverted_index.three | 91 |
| abstract_inverted_index.using | 60 |
| abstract_inverted_index.(IQR), | 89 |
| abstract_inverted_index.(IoT). | 134 |
| abstract_inverted_index.Hjorth | 92 |
| abstract_inverted_index.Things | 133 |
| abstract_inverted_index.alpha, | 69 |
| abstract_inverted_index.during | 34 |
| abstract_inverted_index.forest | 65 |
| abstract_inverted_index.mental | 11, 38, 48, 101 |
| abstract_inverted_index.method | 6 |
| abstract_inverted_index.random | 64 |
| abstract_inverted_index.range, | 86 |
| abstract_inverted_index.signal | 99 |
| abstract_inverted_index.states | 49 |
| abstract_inverted_index.tasks. | 39 |
| abstract_inverted_index.develop | 41 |
| abstract_inverted_index.explore | 55 |
| abstract_inverted_index.further | 122 |
| abstract_inverted_index.model's | 106 |
| abstract_inverted_index.results | 109 |
| abstract_inverted_index.square, | 82 |
| abstract_inverted_index.Internet | 131 |
| abstract_inverted_index.accuracy | 116 |
| abstract_inverted_index.analysis | 107 |
| abstract_inverted_index.applying | 113 |
| abstract_inverted_index.classify | 8 |
| abstract_inverted_index.describe | 23 |
| abstract_inverted_index.dynamics | 29 |
| abstract_inverted_index.ensemble | 57 |
| abstract_inverted_index.features | 20, 77 |
| abstract_inverted_index.forecast | 47 |
| abstract_inverted_index.learning | 58 |
| abstract_inverted_index.temporal | 28 |
| abstract_inverted_index.utilized | 123 |
| abstract_inverted_index.workload | 13 |
| abstract_inverted_index.cognitive | 12 |
| abstract_inverted_index.efficient | 5 |
| abstract_inverted_index.extracted | 95 |
| abstract_inverted_index.obtaining | 19 |
| abstract_inverted_index.skewness, | 83 |
| abstract_inverted_index.subject's | 10 |
| abstract_inverted_index.suggested | 105 |
| abstract_inverted_index.technique | 59 |
| abstract_inverted_index.arithmetic | 102 |
| abstract_inverted_index.automation | 128 |
| abstract_inverted_index.continuous | 25 |
| abstract_inverted_index.parameters | 93 |
| abstract_inverted_index.underlying | 27 |
| abstract_inverted_index.application | 126 |
| abstract_inverted_index.classifier. | 66 |
| abstract_inverted_index.classifiers | 61 |
| abstract_inverted_index.demonstrate | 110 |
| abstract_inverted_index.performance | 36 |
| abstract_inverted_index.techniques, | 115 |
| abstract_inverted_index.Ourobjective | 0 |
| abstract_inverted_index.before-during | 100 |
| abstract_inverted_index.differentiate | 97 |
| abstract_inverted_index.interquartile | 87 |
| abstract_inverted_index.electroencephalography | 31 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5087524850 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I145286018 |
| citation_normalized_percentile.value | 0.13404607 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |