Materials, devices, and systems of on‐skin electrodes for electrophysiological monitoring and human–machine interfaces

H Wu, G Yang, K Zhu, S Liu, W Guo, Z Jiang… - Advanced …, 2021 - Wiley Online Library
On‐skin electrodes function as an ideal platform for collecting high‐quality
electrophysiological (EP) signals due to their unique characteristics, such as stretchability …

Driver fatigue detection systems: A review

G Sikander, S Anwar - IEEE Transactions on Intelligent …, 2018 - ieeexplore.ieee.org
Driver fatigue has been attributed to traffic accidents; therefore, fatigue-related traffic
accidents have a higher fatality rate and cause more damage to the surroundings compared …

In ictu oculi: Exposing ai created fake videos by detecting eye blinking

Y Li, MC Chang, S Lyu - 2018 IEEE International workshop on …, 2018 - ieeexplore.ieee.org
The new developments in deep generative networks have significantly improve the quality
and efficiency in generating realistically-looking fake face videos. In this work, we describe a …

Driver drowsiness detection by applying deep learning techniques to sequences of images

E Magán, MP Sesmero, JM Alonso-Weber, A Sanchis - Applied Sciences, 2022 - mdpi.com
This work presents the development of an ADAS (advanced driving assistance system)
focused on driver drowsiness detection, whose objective is to alert drivers of their drowsy …

In ictu oculi: Exposing ai generated fake face videos by detecting eye blinking

Y Li, MC Chang, S Lyu - ar** us decline the occurrence probability
of traffic accidents and the aim of this research is to develop a novel system for driving stress …

Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …

HV Koay, JH Chuah, CO Chow, YL Chang - Engineering Applications of …, 2022 - Elsevier
Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …

[HTML][HTML] A comprehensive review of approaches to detect fatigue using machine learning techniques

R Hooda, V Joshi, M Shah - Chronic Diseases and Translational Medicine, 2021 - Elsevier
In the past decades, there have been numerous advancements in the field of technology.
This has led to many scientific breakthroughs in the field of medical sciences. In this, rapidly …

Automatic detection of alertness/drowsiness from physiological signals using wavelet-based nonlinear features and machine learning

L Chen, Y Zhao, J Zhang, J Zou - Expert Systems with Applications, 2015 - Elsevier
Physiological signals such as electroencephalogram (EEG) and electrooculography (EOG)
recordings are very important non-invasive measures of detecting a person's …

Using long short term memory and convolutional neural networks for driver drowsiness detection

A Quddus, AS Zandi, L Prest, FJE Comeau - Accident Analysis & Prevention, 2021 - Elsevier
Fatigue negatively affects the safety and performance of drivers on the road. In fact,
drowsiness and fatigue are the cause of a substantial number of motor vehicle accidents …