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Wyświetlanie 1-1 z 1
Tytuł:
EEG signal analysis for monitoring concentration of operators
Autorzy:
Rykała, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/27314223.pdf
Data publikacji:
2023
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
electroencephalography
EEG
signal processing
Fourier analysis
LabVIEW
biofeedback
operator concentration
UGV
Opis:
Often, operators of machines, including unmanned ground vehicles (UGVs) or working machines, are forced to work in unfavorable conditions, such as high tem‐ peratures, continuously for a long period of time. This has a huge impact on their concentration, which usu‐ ally determines the success of many tasks entrusted to them. Electroencephalography (EEG) allows the study of the electrical activity of the brain. It allows the determination, for example, of whether the operator is able to focus on the realization of his tasks. The main goal of this article was to develop an algorithm for determining the state of brain activity by analyzing the EEG signal. For this purpose, methods of EEG sig‐ nal acquisition and processing were described, including EEG equipment and types and location of electrodes. Particular attention was paid to EEG signal acquisition, EEG signal artifacts, and disturbances, and elements of the adult’s correct EEG recording were described in detail. In order to develop the algorithm mentioned, basic types of brain waves were discussed, and exem‐ plary states of brain activity were recorded. The influ‐ ence of technical aspects on the recording of EEG sig‐ nals was also emphasized. Additionally, a block diagram was created which is the basis for the operation of the said algorithm. The LabVIEW environment was used to implement the created algorithm. The results of the research showing the operation of the developed EEG signal analyzer were also presented. Based on the results of the study, the EEG analyzer was able to accurately determine the condition of the examined person and could be used to study the concentration of machine operators.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2023, 17, 1; 30--39
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-1 z 1

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