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Blinkbeteendebaserad trötthetsdetektering

metodutveckling och validering


Electrooculogram (EOG) data was used to develop, adjust and validate a method for drowsiness detection in drivers. The drowsiness detection was based on changes in blink behaviour and classification was made on a four graded scale. The purpose was to detect early signs of drowsiness in order to warn a driver. MATLAB was used for implementation. For adjustment and validatation, two different reference measures were used; driver reported ratings of drowsiness and an electroencephalogram (EEG) based scoring scale. A correspondence of 70 % was obtained between the program and the self ratings and 56 % between the program and the EEG based scoring scale. The results show a possibility to detect drowsiness by analyzing blink behaviour changes, but that inter-individual differences need to be considered. It is also difficult to find a comparable reference measure. The comparability of the blink based scale and the EEG based scale needs further investigation.

Författare

Ulrika Svensson

Lärosäte och institution

Linköpings universitet/Institutionen för medicinsk teknik

Nivå:

"Uppsats för yrkesexamina på grundnivå". Självständigt arbete (examensarbete)om minst 15 högskolepoäng utfört för att erhålla yrkesexamen på grundnivå.

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