[HTML][HTML] Brain computer interfaces for improving the quality of life of older adults and elderly patients

AN Belkacem, N Jamil, JA Palmer, S Ouhbi… - Frontiers in …, 2020 - frontiersin.org
All people experience aging, and the related physical and health changes, including
changes in memory and brain function. These changes may become debilitating leading to …

[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 …

Prognosis for patients with cognitive motor dissociation identified by brain-computer interface

J Pan, Q Xie, P Qin, Y Chen, Y He, H Huang, F Wang… - Brain, 2020 - academic.oup.com
Cognitive motor dissociation describes a subset of patients with disorders of consciousness
who show neuroimaging evidence of consciousness but no detectable command-following …

[HTML][HTML] An adversarial discriminative temporal convolutional network for EEG-based cross-domain emotion recognition

Z He, Y Zhong, J Pan - Computers in biology and medicine, 2022 - Elsevier
Abstract Domain adaptation (DA) tackles the problem where data from the source domain
and target domain have different underlying distributions. In cross-domain (cross-subject or …

[HTML][HTML] A 3D-convolutional neural network framework with ensemble learning techniques for multi-modal emotion recognition

ES Salama, RA El-Khoribi, ME Shoman… - Egyptian Informatics …, 2021 - Elsevier
Nowadays, human emotion recognition is a mandatory task for many human machine
interaction fields. This paper proposes a novel multi-modal human emotion recognition …

Combining facial expressions and electroencephalography to enhance emotion recognition

Y Huang, J Yang, S Liu, J Pan - Future Internet, 2019 - mdpi.com
Emotion recognition plays an essential role in human–computer interaction. Previous
studies have investigated the use of facial expression and electroencephalogram (EEG) …

[HTML][HTML] Managing disorders of consciousness: the role of electroencephalography

Y Bai, Y Lin, U Ziemann - Journal of Neurology, 2021 - Springer
Disorders of consciousness (DOC) are an important but still underexplored entity in
neurology. Novel electroencephalography (EEG) measures are currently being employed …

Machine learning classification of maladaptive rumination and cognitive distraction in terms of frequency specific complexity

S Aydın, B Akın - Biomedical Signal Processing and Control, 2022 - Elsevier
In this study, cognitive and behavioral emotion regulation strategies (ERS) are classified by
using machine learning models driven by a new local EEG complexity approach so called …

An efficient mixture model approach in brain-machine interface systems for extracting the psychological status of mentally impaired persons using EEG signals

NM Krishna, K Sekaran, AVN Vamsi… - Ieee …, 2019 - ieeexplore.ieee.org
We propose an efficient mixture classification technique, which uses
electroencephalography (EEG) signals for establishing a communication channel for the …

Multimodal affective state assessment using fNIRS+ EEG and spontaneous facial expression

Y Sun, H Ayaz, AN Akansu - Brain Sciences, 2020 - mdpi.com
Human facial expressions are regarded as a vital indicator of one's emotion and intention,
and even reveal the state of health and wellbeing. Emotional states have been associated …