Miner Fatigue Detection from Electroencephalogram-Based Relative Power Spectral Topography Using Convolutional Neural Network

Miner Fatigue Detection from Electroencephalogram-Based Relative Power Spectral Topography Using Convolutional Neural Network

Fatigue of miners is caused by intensive workloads, long working hours, and shift-work schedules. It is one of the major factors increasing the risk of safety problems and work mistakes. Examining the detection of miner fatigue is important because it can potentially prevent work accidents and impro...

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Bibliographic Details
Main Authors: Lili Xu, Jizu Li, Ding Feng
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Sensors
Subjects:
fatigue detection
convolutional neural network (CNN)
the relative power spectral density (RPSD)
deep learning
EEG
miners
Online Access:https://www.mdpi.com/1424-8220/23/22/9055

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https://www.mdpi.com/1424-8220/23/22/9055

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