A Hybrid Scheme for Drowsiness Detection Using Wearable Sensors

• Published in: IEEE sensors journal Vol. 19; no. 13; pp. 5119 - 5126
• Main Authors: Mehreen, Aqsa, Anwar, Syed Muhammad, Haseeb, Muhammad, Majid, Muhammad, Ullah, Muhammad Obaid
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accelerometer; Accelerometers; Accuracy; blink analysis; Classifiers; Data acquisition; drowsiness; EEG sensor; Electrocardiography; Electrodes; Electroencephalography; Feature extraction; gyroscope; Head movement; Sensors; Sleep; Sleep deprivation; Sleepiness; spectral power; Support vector machines; Wearable sensors; Wearable technology

The problem addressed in this paper is the detection of drowsiness based on signals acquired using non-invasive and wearable sensors. A combination of signals from electroencephalography (EEG) electrodes, accelerometer, and gyroscope is acquired through a commercially available off-the-shelf headban...