A comprehensive survey on vehicular networking: Communications, applications, challenges, and upcoming research directions

NH Hussein, CT Yaw, SP Koh, SK Tiong… - IEEE Access, 2022 - ieeexplore.ieee.org
Nowadays, advanced communication technologies are being utilized to develop intelligent
transportation management and driving assistance. Through the ability to exchange traffic …

Noninvasive EEG-Based Intelligent Mobile Robots: A Systematic Review

H Li, X Li, JR Millán - IEEE Transactions on Automation Science …, 2024 - ieeexplore.ieee.org
Brain-controlled mobile robotics can provide restoration of mobility for individuals with
severe physical disabilities and empower healthy people with a broader reachable range in …

Robust predictive control for EEG-based brain–robot teleoperation

H Li, L Bi, X Li, H Gan - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
Brain-teleoperation robot control ensures that human beings interact with telepresence
mobile systems through the brain neural signals. In this study, a hierarchical robust …

EEGGAN-Net: enhancing EEG signal classification through data augmentation

J Song, Q Zhai, C Wang, J Liu - Frontiers in Human Neuroscience, 2024 - frontiersin.org
Background Emerging brain-computer interface (BCI) technology holds promising potential
to enhance the quality of life for individuals with disabilities. Nevertheless, the constrained …

Gender differences in EEG responses to color and black-white images: implications for neuromarketing strategies

A Hassani, A Hekmatmanesh, AM Nasrabadi - IEEE Access, 2023 - ieeexplore.ieee.org
Analyzing the decision of different genders during shop** is an interesting topic in the
neuromarketing industry. This study explores the EEG signal acquisition of twenty subjects …

Characterisation of cognitive load using machine learning classifiers of electroencephalogram data

Q Wang, D Smythe, J Cao, Z Hu, KJ Proctor, AP Owens… - Sensors, 2023 - mdpi.com
A high cognitive load can overload a person, potentially resulting in catastrophic accidents. It
is therefore important to ensure the level of cognitive load associated with safety-critical …

FB-CCNN: A Filter Bank Complex Spectrum Convolutional Neural Network with Artificial Gradient Descent Optimization

D Xu, F Tang, Y Li, Q Zhang, X Feng - Brain Sciences, 2023 - mdpi.com
The brain–computer interface (BCI) provides direct communication between human brains
and machines, including robots, drones and wheelchairs, without the involvement of …

Physiological Noise Filtering in Functional Near-Infrared Spectroscopy Signals Using Wavelet Transform and Long-Short Term Memory Networks

SH Yoo, G Huang, KS Hong - Bioengineering, 2023 - mdpi.com
Activated channels of functional near-infrared spectroscopy are typically identified using the
desired hemodynamic response function (dHRF) generated by a trial period. However, this …

Adversarial Neural Network Training for Secure and Robust Brain-to-Brain Communication

H Ahmadi, A Kuhestani, L Mesin - IEEE Access, 2024 - ieeexplore.ieee.org
In the rapidly evolving domain of brain-to-brain communication, safeguarding the
transmission of information against adversarial threats is paramount. This study introduces …

EEG-Based Classification of Spoken Words Using Machine Learning Approaches

D Alonso-Vázquez, O Mendoza-Montoya, R Caraza… - Computation, 2023 - mdpi.com
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that affects the nerve
cells in the brain and spinal cord. This condition leads to the loss of motor skills and, in many …