Open AccessOn the person and psychophysiological state identification using electroencephalogram parameters
Author(s) -
Alexey Andreevich Nigrey,
A. E. Sulavko,
A. E. Samotuga,
D. P. Inivatov
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1546/1/012092
Subject(s) - electroencephalography , psychology , naive bayes classifier , artificial intelligence , identification (biology) , pattern recognition (psychology) , computer science , speech recognition , psychiatry , botany , support vector machine , biology
The development of methods and technologies for the automatic determination of the psychophysiological state (PPS) of a person is an actual scientific and technical task. Early detection of the fact that the subject is in a sleepy state or in a state of intoxication at the workplace will help to avoid accidents, harm to life, health, and causing losses. In this work the EEG data of 30 subjects in normal, sleepy conditions and a state of mild intoxication were collected. As a result of the spectral and correlation analysis of the EEG data features were selected. An amount of information about the difference of the investigated states contained in the features was determined. A computational experiment on the recognition of human state according to EEG data based on the “naive” Bayes classifier was conducted. The following error level was achieved: 10.9% when recognizing the state of “norm” and “intoxication”; 0.2% when recognizing the status of “normal” and “falling asleep.”