EEG based emotion recognition: A tutorial and review

X Li, Y Zhang, P Tiwari, D Song, B Hu, M Yang… - ACM Computing …, 2022 - dl.acm.org
Emotion recognition technology through analyzing the EEG signal is currently an essential
concept in Artificial Intelligence and holds great potential in emotional health care, human …

[HTML][HTML] Past, present, and future of EEG-based BCI applications

K Värbu, N Muhammad, Y Muhammad - Sensors, 2022 - mdpi.com
An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that
provides a pathway between the brain and external devices by interpreting EEG. EEG …

EEG based stress monitoring

X Hou, Y Liu, O Sourina, YRE Tan… - … on systems, man …, 2015 - ieeexplore.ieee.org
Everyone experiences stress in life. Moderate stress can be beneficial to human, however,
excessive stress is harmful to the health. To monitor stress, different methods can be used. In …

[HTML][HTML] Tuning pathological brain oscillations with neurofeedback: a systems neuroscience framework

T Ros, B J. Baars, RA Lanius… - Frontiers in human …, 2014 - frontiersin.org
Neurofeedback (NFB) is emerging as a promising technique that enables self-regulation of
ongoing brain oscillations. However, despite a rise in empirical evidence attesting to its …

A review of the use of psychophysiological methods in game research

JM Kivikangas, G Chanel, B Cowley… - journal of gaming & …, 2011 - intellectdiscover.com
This article reviews the psychophysiological method in game research. Psychophysiological
measurements provide an objective, continuous, real-time, noninvasive, precise and …

Real-time mental arithmetic task recognition from EEG signals

Q Wang, O Sourina - IEEE Transactions on Neural Systems and …, 2013 - ieeexplore.ieee.org
Electroencephalography (EEG)-based monitoring the state of the user's brain functioning
and giving her/him the visual/audio/tactile feedback is called neurofeedback technique, and …

[PDF][PDF] Analysis of EEG signals using nonlinear dynamics and chaos: a review

G Rodriguez-Bermudez… - Applied mathematics …, 2015 - naturalspublishing.com
Nonlinear dynamics and chaos theory have been used in neurophysiology with the aim to
understand the complex brain activity from electroencephalographic (EEG) signals …

[HTML][HTML] Brain-machine interfaces beyond neuroprosthetics

KA Moxon, G Foffani - Neuron, 2015 - cell.com
The field of invasive brain-machine interfaces (BMIs) is typically associated with
neuroprosthetic applications aiming to recover loss of motor function. However, BMIs also …

Real-time subject-dependent EEG-based emotion recognition algorithm

Y Liu, O Sourina - Transactions on Computational Science XXIII: Special …, 2014 - Springer
In this paper, we proposed a real-time subject-dependent EEG-based emotion recognition
algorithm and tested it on experiments' databases and the benchmark database DEAP. The …

Real-time fractal-based valence level recognition from EEG

Y Liu, O Sourina - Transactions on computational science XVIII: special …, 2013 - Springer
Emotions are important in human-computer interaction. Emotions could be classified based
on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of …