Application of Machine Learning Algorithm for Mental State Attention Classification Based on Electroencephalogram Signals

Katon Suwida*, Shintami Chusnul Hidayati, Riyanarto Sarno

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Technological developments provide a new work environment where the human role is reduced to that of a passive observer. Risk in the workplace might result from a person's incapacity to maintain attention and concentration while doing passive control activities. Passive brain-computer interface (BCI) can be used to monitor mental attention status in humans (focused, unfocused, and drowsy) using electroencephalogram (EEG) signals. This study proposes using BCI to detect the level of mental attention status based on EEG signals using machine learning. In designing the architecture of this study, the EEG signal data has been decomposed by the Discrete Wavelet Transform (DWT) decomposition process with 4 decomposition levels and using the Daubechies family (dB). The signal decomposition results are extracted using several statistical features, which are then used for machine learning model features. The Xtreme Gradient Boost (XGBoost) algorithm was used to perform the classification task. The XGBoost model produced accuracy results of 99% (best) on individual subject tests and 98% (average) on all subjects.

Original languageEnglish
Title of host publicationICCoSITE 2023 - International Conference on Computer Science, Information Technology and Engineering
Subtitle of host publicationDigital Transformation Strategy in Facing the VUCA and TUNA Era
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages354-358
Number of pages5
ISBN (Electronic)9798350320954
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Computer Science, Information Technology and Engineering, ICCoSITE 2023 - Jakarta, Indonesia
Duration: 16 Feb 2023 → …

Publication series

NameICCoSITE 2023 - International Conference on Computer Science, Information Technology and Engineering: Digital Transformation Strategy in Facing the VUCA and TUNA Era

Conference

Conference2023 International Conference on Computer Science, Information Technology and Engineering, ICCoSITE 2023
Country/TerritoryIndonesia
CityJakarta
Period16/02/23 → …

Keywords

  • Brain-computer interface (BCI)
  • Discrete Wavelet Transform (DWT)
  • Electroencephalogram (EEG)
  • Machine Learning
  • Xtreme Gradient Boost (XGBoost)

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