[HTML][HTML] Human emotion recognition: Review of sensors and methods
Automated emotion recognition (AEE) is an important issue in various fields of activities
which use human emotional reactions as a signal for marketing, technical equipment, or …
which use human emotional reactions as a signal for marketing, technical equipment, or …
[HTML][HTML] Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations
Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …
and modalities using questionnaires, physical signals, and physiological signals. Recently …
Emotions recognition using EEG signals: A survey
SM Alarcao, MJ Fonseca - IEEE transactions on affective …, 2017 - ieeexplore.ieee.org
Emotions have an important role in daily life, not only in human interaction, but also in
decision-making processes, and in the perception of the world around us. Due to the recent …
decision-making processes, and in the perception of the world around us. Due to the recent …
[HTML][HTML] EEG-based emotion classification using a deep neural network and sparse autoencoder
Emotion classification based on brain–computer interface (BCI) systems is an appealing
research topic. Recently, deep learning has been employed for the emotion classifications of …
research topic. Recently, deep learning has been employed for the emotion classifications of …
[HTML][HTML] EEG-based emotion recognition: Review of commercial EEG devices and machine learning techniques
Emotion recognition based on electroencephalography (EEG) signal features is now one of
the booming big data research areas. As the number of commercial EEG devices in the …
the booming big data research areas. As the number of commercial EEG devices in the …
A review, current challenges, and future possibilities on emotion recognition using machine learning and physiological signals
The seminal work on Affective Computing in 1995 by Picard set the base for computing that
relates to, arises from, or influences emotions. Affective computing is a multidisciplinary field …
relates to, arises from, or influences emotions. Affective computing is a multidisciplinary field …
[HTML][HTML] Review and classification of emotion recognition based on EEG brain-computer interface system research: a systematic review
Recent developments and studies in brain-computer interface (BCI) technologies have
facilitated emotion detection and classification. Many BCI studies have sought to investigate …
facilitated emotion detection and classification. Many BCI studies have sought to investigate …
Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy–TOPSIS methods
Context and background Corona virus (COVID) has rapidly gained a foothold and caused a
global pandemic. Particularists try their best to tackle this global crisis. New challenges …
global pandemic. Particularists try their best to tackle this global crisis. New challenges …
[HTML][HTML] Subject independent emotion recognition from EEG using VMD and deep learning
Emotion recognition from Electroencephalography (EEG) is proved to be a good choice as it
cannot be mimicked like speech signals or facial expressions. EEG signals of emotions are …
cannot be mimicked like speech signals or facial expressions. EEG signals of emotions are …
[HTML][HTML] Review on emotion recognition based on electroencephalography
H Liu, Y Zhang, Y Li, X Kong - Frontiers in Computational …, 2021 - frontiersin.org
Emotions are closely related to human behavior, family and society. Since changes in
emotions can cause differences in electroencephalography (EEG) signals, EEG signals can …
emotions can cause differences in electroencephalography (EEG) signals, EEG signals can …