AIMC Topic: Automobile Driving

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Single-Channel Real-Time Drowsiness Detection Based on Electroencephalography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The need of a reliable drowsiness detection system is arising today, as drowsiness is considered as a major cause for accidents as much as alcohol. In this paper, we propose a real-time drowsiness detection algorithm based on a single-channel electro...

Online SVM-based personalizing method for the drowsiness detection of drivers.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Inter-driver variation is one of major problems of the drowsiness detecting system-based on physiological signals. This paper proposes an online support vector machine (OSVM)-based method to solve the problem by the inter-driver variation. The method...

Detection of steering direction using EEG recordings based on sample entropy and time-frequency analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Monitoring driver's intentions beforehand is an ambitious aim, which will bring a huge impact on the society by preventing traffic accidents. Hence, in this preliminary study we recorded high resolution electroencephalography (EEG) from 5 subjects wh...

Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals.

Studies in health technology and informatics
Machine learning algorithms play an important role in computer science research. Recent advancement in sensor data collection in clinical sciences lead to a complex, heterogeneous data processing, and analysis for patient diagnosis and prognosis. Dia...

Driving, navigation, and vehicular technology: experiences of older drivers and their co-pilots.

Traffic injury prevention
OBJECTIVE: The objective of this article is to explore relationship between older drivers and their passengers (co-pilots) and potential implications of in-vehicle navigation technology on their driving safety.