There are several human activities where the awareness and conscious control is a very important factor: vehicle driving, heavy equipment operation, hazardous materials manipulation. In these cases drowsiness can be the cause of injury or even death. For example car driver drowsiness is one of the causes of serious traffic accidents, which makes this an area of a significant importance. Continuous monitoring of driver’s or operator’s drowsiness is of great importance if we want to reduce accidents due to operator’s fault. If drowsiness is detected in time, a significant part of these accidents could be successfully prevented. In the last years various methods were tested, based on the use of: heart rate variability, video monitoring of the eyes, EEG, EMG and ECG signals. Our research is based on the study of EEG and EMG signals and aims to develop algorithms capable to detect features specific to the drowsiness state and decide the moment in which the driver or operator should be alerted.
drowsiness alert, EEG, EMG, fuzzy decision algorithm.
Simona Dzitac, Tiberiu Vesselenyi, Laurentiu Popper, Ioan Moga, Calin Dinu Secui, "Fuzzy Algorithm for Human Drowsiness Detection Devices", Studies in Informatics and Control, ISSN 1220-1766, vol. 19(4), pp. 419-426, 2010. https://doi.org/10.24846/v19i4y201010
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