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Vigilance detection method for high-speed rail using wireless wearable EEG collection technology based on low-rank matrix decomposition

Vigilance detection method for high-speed rail using wireless wearable EEG collection technology based on low-rank matrix decomposition

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With the development of rail transit, driver vigilance is increasingly important in railway safety. A vigilance detection method based on high-speed rail (HSR) is presented in this study. The proposed method includes three main parts: (i) a wireless wearable electroencephalography (EEG) collection module; (ii) HSR driver's vigilance detection module; and (iii) an early warning module. Drivers’ vigilance is monitored using eight EEG channels. A low-rank matrix decomposition (also called robust principal component analysis) algorithm is used to classify EEG signals which are collected through wireless wearable EEG collection technology. The warning module will sound an alarm and the early warning begins to message the train control centre if the driver is judged as fatigue. The method was tested on driving EEG data from ten different drivers and reached 99.4% correct classification in a 9 s time window. The feasibility of the proposed vigilance-detecting method for HSR safety is demonstrated through simulation and test results.

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