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Detection of pilot body conditions by biometric sensors
Jakubec, Jakub ; Cigánek, Jan (referee) ; Chlebek, Jiří (advisor)
This master 's thesis deals with the detection of the state of the pilot using biometric sensors. The theoretical part describes various physiological states and types of sensors used for monitoring. Studies dealing with sleep detectioin and ways to detect drowsiness and sleep are presented here. The practical section focuses on gathering data from the actual aircraft environment and analyzing it. The results of the practical part show that the technology used has great potential and pilots are open to this technology. This technology would significantly improve flight safety.
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Analysis of electroencephalograms
Gajdoš, Martin ; Rozman, Jiří (referee) ; Kolářová, Jana (advisor)
Electroencephalography is sensitive diagnostic method for measuring electric potentials generated by brain. In this project are described the properties of the EEG signal and methods of EEG measuring, processing and evaluating. Also the noise sources and methods for noise removing are described. The project deals in the second part with detection of drowsiness and microsleep from driver’s EEG. At first theoretically, then is shown the practical measurement of EEG on volunteers. During the measurement was intention to induce drowsiness and microsleep. Finally is described the processing of measured EEG signals and the results are visualized.
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Analysis of electroencephalograms
Gajdoš, Martin ; Rozman, Jiří (referee) ; Kolářová, Jana (advisor)
Electroencephalography is sensitive diagnostic method for measuring electric potentials generated by brain. In this project are described the properties of the EEG signal and methods of EEG measuring, processing and evaluating. Also the noise sources and methods for noise removing are described. The project deals in the second part with detection of drowsiness and microsleep from driver’s EEG. At first theoretically, then is shown the practical measurement of EEG on volunteers. During the measurement was intention to induce drowsiness and microsleep. Finally is described the processing of measured EEG signals and the results are visualized.
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Identification of Driver's Drowsiness Using Driving Information and EEG
Jiřina, Marcel ; Novotný, S. ; Bouchner, P.
This report summarizes the first results with identification of sleepy state in drivers. The driving information as the deviation from the centerline of road and the steering wheel position as well as two-point eeg was used. The process consists of preprocessing data, in fact a transformation into form proper for classification, and a classification into one of two classes, wakefulness and drowsiness. Results show that it is possible to distinguish these two states with relatively large error, which possibly can be tackled by the use of proper methodology.
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