Results 31 to 40 of about 31,323 (271)
Safety profile of oxcarbazepine: results from a prescription-event monitoring study [PDF]
, 2010 Purpose: To monitor safety of oxcarbazepine, prescribed in primary care in England, using prescription-event monitoring (PEM). Methods: Postmarketing surveillance using observational cohort technique of PEM.
Buggy, Y. +3 more
core +1 more source
A Survey on State-of-the-Art Drowsiness Detection Techniques
IEEE Access, 2019 Drowsiness or fatigue is a major cause of road accidents and has significant implications for road safety. Several deadly accidents can be prevented if the drowsy drivers are warned in time.
Muhammad Ramzan +5 more
doaj +1 more source
Detecting Distracted Driving with Deep Learning [PDF]
, 2017 © Springer International Publishing AG 2017Driver distraction is the leading factor in most car crashes and near-crashes. This paper discusses the types, causes and impacts of distracted driving.
A Nabo +9 more
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Big data analytics:Computational intelligence techniques and application areas [PDF]
, 2020 Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization ...
Doctor, Faiyaz +4 more
core +2 more sources
International Journal of Engineering and Advanced Technology, 2020 Melbourne is one of the liveliest cities in the world. It has a well efficient transport system, supported by a vast network of trams. Therefore, the mental health and stress level of the tram drivers plays a crucial role in the safety of the passengers.
Suriya Kumar S, Kishor R, J.Kalaivani
openaire +1 more source
Protecting privacy of users in brain-computer interface applications [PDF]
, 2019 Machine learning (ML) is revolutionizing research and industry. Many ML applications rely on the use of large amounts of personal data for training and inference.
Agarwal, Anisha +6 more
core +2 more sources
IET Intelligent Transport Systems, 2021 Detecting drowsiness in drivers while driving is extremely important to avoid possible accidents and reduce the fatality rate due to drivers sleeping at the wheel.
Venkata Phanikrishna Balam +2 more
doaj +1 more source
Odhad únavy člověka: využitelnost systémů dopravy ve vnitřním prostředí [PDF]
, 2018 Fatigue monitoring is nowadays domain in traffic and transportation (e.g. system for driver's sleepness monitoring in cars or in trains). People working in offices are affected by fatigue too, but there is no general system that is able to monitor it ...
Kohout, Jan, Mareš, Jan
core +1 more source
Drowsiness Detection of Driver
International Journal of Advanced Research in Science, Communication and Technology, 2022 Today Many car accidents are caused in significant part by driver weariness. According to recent figures, fatigue-related collisions result in 1,200 fatalities and 76,000 injuries per year. The evolution of the development of technologies for detecting and avoiding drowsiness at the wheel is a major challenge in the field of accident avoidance systems.
null Vaishnavi Shivdas +3 more
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EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features [PDF]
, 2017 Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first time, it is applied to BCI regression problems, an important category of BCI
Gordon, Stephen +5 more
core +1 more source