Abstract
Electrooculogram (EOG), while being a source of useful information. Many researches and applications such as Human computer interaction (HCI) and physiological state monitoring rely match more on it then other resources like video surveillance. In our work we’re interested in awareness level classification for driver drowsiness detection, in the purpose of improving road security. However, EOG acquisition requires placing electrodes around eye’s subject all the time which is not comfortable and convenient for many applications. Therefore, we propose a generation of a Bio-inspired EOG signal (pseudo EOG) using video camera. As for EOG signal, the bio-inspired one contains useful information of eye state and movements in time. Critical features were extracted or calculated from the bio-inspired EOG signal and used as inputs of a fuzzy logic classification of the awareness level in time.
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Yahia Lahssene, Y., Keche, M., Ouamri, A. (2020). Bio-Inspired EOG Generation from Video Camera: Application to Driver’s Awareness Monitoring. In: Bouhlel, M., Rovetta, S. (eds) Proceedings of the 8th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT’18), Vol.1. SETIT 2018. Smart Innovation, Systems and Technologies, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-030-21005-2_39
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DOI: https://doi.org/10.1007/978-3-030-21005-2_39
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