Oliveira, LicínioCardoso, JaimeLourenço, AndréAhlstrom, Christer2019-04-162019-04-162018OLIVEIRA, Licínio; [et al] – Driver drowsiness detection: a comparison between intrusive and non-intrusive signal acquisition methods. In Proceedings of the 2018 7th European Workshop on Visual Information Processing (EUVIP). Tampere, Finland: IEEE, 2018. ISSN 2164-974X. Pp. 1-62164-974X2471-8963http://hdl.handle.net/10400.21/9870Driver drowsiness is a major cause of road accidents, many of which result in fatalities. A solution to this problem is the inclusion of a drowsiness detector in vehicles to alert the driver if sleepiness is detected. To detect drowsiness, physiologic, behavioral (visual) and vehicle-based methods can be used, however, only measures that can be acquired non-intrusively are viable in a real life application. This work uses data from a real-road experiment with sleep deprived drivers to compare the performance of driver drowsiness detection using intrusive acquisition methods, namely electrooculogram (EOG), with camera based, non-intrusive, methods. A hybrid strategy, combining the described methods with electrocardiogram (ECG) measures, is also evaluated. Overall, the obtained results show that drowsiness detection performance is similar using non-intrusive camera based measures or intrusive EOG measures. The detection performance increases when combining two methods (ECG + visual) or (ECG + EOG).engDriver drowsinessCamera-based methodsECGEOGconference object