EEG‐based emotion recognition: a state‐of‐the‐art review of current trends and opportunities
NS Suhaimi, J Mountstephens… - Computational …, 2020 - Wiley Online Library
Emotions are fundamental for human beings and play an important role in human cognition.
Emotion is commonly associated with logical decision making, perception, human …
Emotion is commonly associated with logical decision making, perception, human …
Review on emotion recognition based on electroencephalography
H Liu, Y Zhang, Y Li, X Kong - Frontiers in Computational …, 2021 - frontiersin.org
Emotions are closely related to human behavior, family, and society. Changes in emotions
can cause differences in electroencephalography (EEG) signals, which show different …
can cause differences in electroencephalography (EEG) signals, which show different …
A comprehensive survey of driving monitoring and assistance systems
MQ Khan, S Lee - Sensors, 2019 - mdpi.com
Improving a vehicle driver's performance decreases the damage caused by, and chances of,
road accidents. In recent decades, engineers and researchers have proposed several …
road accidents. In recent decades, engineers and researchers have proposed several …
Increasing trend of wearables and multimodal interface for human activity monitoring: A review
Activity recognition technology is one of the most important technologies for life-logging and
for the care of elderly persons. Elderly people prefer to live in their own houses, within their …
for the care of elderly persons. Elderly people prefer to live in their own houses, within their …
A multimodal approach to estimating vigilance using EEG and forehead EOG
Objective. Covert aspects of ongoing user mental states provide key context information for
user-aware human computer interactions. In this paper, we focus on the problem of …
user-aware human computer interactions. In this paper, we focus on the problem of …
A comparative study of state-of-the-art driving strategies for autonomous vehicles
The autonomous vehicle is regarded as a promising technology with the potential to
reshape mobility and solve many traffic issues, such as accessibility, efficiency …
reshape mobility and solve many traffic issues, such as accessibility, efficiency …
Driver fatigue detection based on convolutional neural networks using em‐CNN
Z Zhao, N Zhou, L Zhang, H Yan, Y Xu… - Computational …, 2020 - Wiley Online Library
With a focus on fatigue driving detection research, a fully automated driver fatigue status
detection algorithm using driving images is proposed. In the proposed algorithm, the …
detection algorithm using driving images is proposed. In the proposed algorithm, the …
Sensor applications and physiological features in drivers' drowsiness detection: A review
A Chowdhury, R Shankaran, M Kavakli… - IEEE sensors …, 2018 - ieeexplore.ieee.org
Drowsiness in drivers has become a serious cause of concern due to the occurrences of a
large number of fatalities on the road each year. Lives of pedestrians and passengers are …
large number of fatalities on the road each year. Lives of pedestrians and passengers are …
Learning CNN features from DE features for EEG-based emotion recognition
Recently, deep neural networks (DNNs) have shown the remarkable success of feature
representations in computer vision, audio analysis, and natural language processing …
representations in computer vision, audio analysis, and natural language processing …
Functional connectivity analysis of mental fatigue reveals different network topological alterations between driving and vigilance tasks
Despite the apparent importance of mental fatigue detection, a reliable application is
hindered due to the incomprehensive understanding of the neural mechanisms of mental …
hindered due to the incomprehensive understanding of the neural mechanisms of mental …