Neural decoding of EEG signals with machine learning: a systematic review

M Saeidi, W Karwowski, FV Farahani, K Fiok, R Taiar… - Brain Sciences, 2021 - mdpi.com
Electroencephalography (EEG) is a non-invasive technique used to record the brain's
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …

Review of techniques and challenges of human and organizational factors analysis in maritime transportation

B Wu, TL Yip, X Yan, CG Soares - Reliability Engineering & System Safety, 2022 - Elsevier
This paper summarises the advanced techniques adopted for the analysis of human and
organizational factors, which are the predominant factors in maritime accidents, and the …

A review of psychophysiological measures to assess cognitive states in real-world driving

M Lohani, BR Payne, DL Strayer - Frontiers in human neuroscience, 2019 - frontiersin.org
As driving functions become increasingly automated, motorists run the risk of becoming
cognitively removed from the driving process. Psychophysiological measures may provide …

A systematic review of physiological measures of mental workload

D Tao, H Tan, H Wang, X Zhang, X Qu… - International journal of …, 2019 - mdpi.com
Mental workload (MWL) can affect human performance and is considered critical in the
design and evaluation of complex human-machine systems. While numerous physiological …

Classification of drivers' mental workload levels: Comparison of machine learning methods based on ecg and infrared thermal signals

D Cardone, D Perpetuini, C Filippini, L Mancini… - Sensors, 2022 - mdpi.com
Mental workload (MW) represents the amount of brain resources required to perform
concurrent tasks. The evaluation of MW is of paramount importance for Advanced Driver …

Recognition of the mental workloads of pilots in the cockpit using EEG signals

A Hernández-Sabaté, J Yauri, P Folch, MÀ Piera… - Applied Sciences, 2022 - mdpi.com
The commercial flightdeck is a naturally multi-tasking work environment, one in which
interruptions are frequent come in various forms, contributing in many cases to aviation …

A systematic review of in-vehicle physiological indices and sensor technology for driver mental workload monitoring

AK Sriranga, Q Lu, S Birrell - Sensors, 2023 - mdpi.com
The concept of vehicle automation ceases to seem futuristic with the current advancement of
the automotive industry. With the introduction of conditional automated vehicles, drivers are …

Recognition of driver's mental workload based on physiological signals, a comparative study

J Huang, Y Liu, X Peng - Biomedical Signal Processing and Control, 2022 - Elsevier
It tends to invite road accidents for automotive drivers when they drive at a too high or too
low level of mental workload. So it's rewarding to recognize driver's mental workload so that …

Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders

S Yang, Z Yin, Y Wang, W Zhang, Y Wang… - Computers in biology and …, 2019 - Elsevier
To estimate the reliability and cognitive states of operator performance in a human-machine
collaborative environment, we propose a novel human mental workload (MW) recognizer …

A systematic review on the influence factors, measurement, and effect of driver workload

J Ma, Y Wu, J Rong, X Zhao - Accident Analysis & Prevention, 2023 - Elsevier
Driver workload (DWL) is an important factor that needs to be considered in the study of
traffic safety. The research focus on DWL has undergone certain shifts with the rapid …