State-of-the-art on brain-computer interface technology

J Peksa, D Mamchur - Sensors, 2023 - mdpi.com
This paper provides a comprehensive overview of the state-of-the-art in brain–computer
interfaces (BCI). It begins by providing an introduction to BCIs, describing their main …

Salient arithmetic data extraction from brain activity via an improved deep network

N Khaleghi, S Hashemi, SZ Ardabili, S Sheykhivand… - Sensors, 2023 - mdpi.com
Interpretation of neural activity in response to stimulations received from the surrounding
environment is necessary to realize automatic brain decoding. Analyzing the brain …

A novel approach for automatic detection of driver fatigue using EEG signals based on graph convolutional networks

SZ Ardabili, S Bahmani, LZ Lahijan, N Khaleghi… - Sensors, 2024 - mdpi.com
Nowadays, the automatic detection of driver fatigue has become one of the important
measures to prevent traffic accidents. For this purpose, a lot of research has been conducted …

[HTML][HTML] Automatic recognition of multiple emotional classes from EEG signals through the use of graph theory and convolutional neural networks

F Mohajelin, S Sheykhivand, A Shabani… - Sensors (Basel …, 2024 - pmc.ncbi.nlm.nih.gov
Emotion is a complex state caused by the functioning of the human brain in relation to
various events, for which there is no scientific definition. Emotion recognition is traditionally …

Attention mechanisms in convolutional neural networks for nitrogen treatment detection in tomato leaves using hyperspectral images

B Benmouna, R Pourdarbani, S Sabzi… - Electronics, 2023 - mdpi.com
Nitrogen is an essential macronutrient for the growth and development of tomatoes.
However, excess nitrogen fertilization can affect the quality of tomato fruit, making it …

Generating personalized facial emotions using emotional EEG signals and conditional generative adversarial networks

M Esmaeili, K Kiani - Multimedia Tools and Applications, 2024 - Springer
Facial expressions are one of the most effective and straightforward ways of conveying our
emotions and intentions. Therefore, it is crucial to conduct research aimed at developing a …

[HTML][HTML] Enhanced cross-dataset electroencephalogram-based emotion recognition using unsupervised domain adaptation

MN Imtiaz, N Khan - Computers in Biology and Medicine, 2025 - Elsevier
Emotion recognition holds great promise in healthcare and in the development of affect-
sensitive systems such as brain–computer interfaces (BCIs). However, the high cost of …

Towards Implementation of Emotional Intelligence in Human–Machine Collaborative Systems

M Markov, Y Kalinin, V Markova, T Ganchev - Electronics, 2023 - mdpi.com
Social awareness and relationship management components can be seen as a form of
emotional intelligence. In the present work, we propose task-related adaptation on the …

[HTML][HTML] An Ensemble Deep Learning Approach for EEG-Based Emotion Recognition Using Multi-Class CSP

B Yousefipour, V Rajabpour, H Abdoljabbari… - Biomimetics, 2024 - mdpi.com
In recent years, significant advancements have been made in the field of brain–computer
interfaces (BCIs), particularly in the area of emotion recognition using EEG signals. The …

[HTML][HTML] Emotion Recognition Using EEG Signals through the Design of a Dry Electrode Based on the Combination of Type 2 Fuzzy Sets and Deep Convolutional …

S Mounesi Rad, S Danishvar - Biomimetics, 2024 - mdpi.com
Emotion is an intricate cognitive state that, when identified, can serve as a crucial
component of the brain–computer interface. This study examines the identification of two …