Microsleep detection of automobile drivers using electrocardiogram signal

• Main Authors: Nor Shahrudin, Nur Shahirah, Sidek, Khairul Azami, Jalaludin, Muhammad Rasydan, Nazmi Asna, Nur Aaina Nazihah
• Other Authors: Liatsis, Panos
• Format: Book Chapter
• Language: English
• Published: Springer Nature 2022
• Subjects: TK7885 Computer engineering
• Online Access: http://irep.iium.edu.my/97193/1/526900_1_En_18_Chapter_OnlinePDF.pdf; http://irep.iium.edu.my/97193/; https://link.springer.com/book/10.1007/978-3-030-97255-4

Microsleep can happen in any situations which could lead to accidents due to the driver’s fatigue. One of the studies that have been done on observing the occurrence of microsleep is by analysing the electrocardiogram (ECG) signal. This study proposed to develop a steering wheel that extracts ECG signal from a driver in preventing microsleep through the data acquisition, pre-processing, feature extraction and classification stages. Firstly, the ECG signals were collected in normal and drowsy states. Then, the signals were filtered using the Savitzky Golay filter and Pan Tompkins’s algorithmwere selected to extract the R peak. The data was analysed using four classifications which are RR interval (RRI), standard deviation of normal to normal (SDNN), root mean square of successive differences (RMSSD) and p-value. Consequently, ECG in steering wheel managed to display a distinct difference for both states through all classifications, simultaneously capable in detecting the occurrence of microsleep.