Results 11 to 20 of about 51,424 (265)
EEG-Based Classification of the Driver Alertness State
Current Directions in Biomedical Engineering, 2020 GMLVQ (Generalized Matrix Relevance Learning Vector Quantization) is a method of machine learning with an adaptive metric. While training, the prototype vectors as well as the weight matrix of the metric are adapted simultaneously.
Golz Martin +2 more
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Proceedings of the 25th Symposium on Operating Systems Principles, 2015 Portable computing devices have fast multi-core processors, large memories, and many on-board sensors and radio interfaces, but are often limited by their energy consumption. Traditional power management subsystems have been extended for smartphones and other portable devices, with the intention of maximizing the time that the devices are in a low ...
Matthew Lentz +2 more
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Intrusions of a drowsy mind: Neural markers of phenomenological unpredictability
Frontiers in Psychology, 2015 The transition from a relaxed to a drowsy state of mind is often accompanied by hypnagogic experiences: most commonly, perceptual imagery, but also linguistic intrusions, i.e. the sudden emergence of unpredictable anomalies in the stream of inner speech.
Valdas eNoreika +8 more
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Frontiers in Physiology, 2020 We previously constructed a perspiration ratemeter for the measurement of palmar sweating in human subjects. Although galvanic skin response (GSR) has been used to evaluate emotional responses in human subjects, little is known about the relationships ...
Hideya Momose +5 more
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Pediatric Neurology Briefs, 2014 Investigators from Sapienza University, Italy, studied the prevalence and treatment of sleep disorders in children with migraine.
J Gordon Millichap, John J Millichap
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Drowsiness, counter-measures to drowsiness, and the risk of a motor vehicle crash [PDF]
Injury Prevention, 2001 Objectives—Knowledge of how different indicators of drowsiness affect crash risk might be useful to drivers. This study sought to estimate how drowsiness related factors, and factors that might counteract drowsiness, are related to the risk of a crash.
P, Cummings +3 more
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Exploring Monitoring Systems Data for Driver Distraction and Drowsiness Research
Sensors, 2020 Driver inattention is a major contributor to road crashes. The emerging of new driver monitoring systems represents an opportunity for researchers to explore new data sources to understand driver inattention, even if the technology was not developed with
António Lobo +2 more
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Portable Drowsiness Detection through Use of a Prefrontal Single-Channel Electroencephalogram
Sensors, 2018 Drowsiness detection has been studied in the context of evaluating products, assessing driver alertness, and managing office environments. Drowsiness level can be readily detected through measurement of human brain activity. The electroencephalogram (EEG)
Mikito Ogino, Yasue Mitsukura
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PLoS ONE, 2023 Driver drowsiness is a widely recognized cause of motor vehicle accidents. Therefore, a reduction in drowsy driving crashes is required. Many studies evaluating the crash risk of drowsy driving and developing drowsiness detection systems, have used ...
Yuji Uchiyama +7 more
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Journal of Advanced Transportation, 2021 Contributions of measurements for detecting drowsy driving are determined by calculation parameters, which are directly related to the accuracy of drowsiness detection.
Yifan Sun +5 more
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