[HTML][HTML] Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations

SK Khare, V Blanes-Vidal, ES Nadimi, UR Acharya - Information fusion, 2024 - Elsevier
Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …

Does keystroke dynamics tell us about emotions? A systematic literature review and dataset construction

A Maalej, I Kallel - 2020 16th International Conference on …, 2020 - ieeexplore.ieee.org
There is strong evidence that emotional states affect the Human's performance and decision-
making. Therefore, understanding Human emotions has become of great concern in the field …

Using facial micro-expressions in combination with EEG and physiological signals for emotion recognition

N Saffaryazdi, ST Wasim, K Dileep, AF Nia… - Frontiers in …, 2022 - frontiersin.org
Emotions are multimodal processes that play a crucial role in our everyday lives.
Recognizing emotions is becoming more critical in a wide range of application domains …

Emotion recognition in conversations using brain and physiological signals

N Saffaryazdi, Y Goonesekera, N Saffaryazdi… - Proceedings of the 27th …, 2022 - dl.acm.org
Emotions are complicated psycho-physiological processes that are related to numerous
external and internal changes in the body. They play an essential role in human-human …

Evaluation and assessment of virtual reality-based simulated training: exploring the human–technology frontier

M Akdere, Y Jiang, FD Lobo - European Journal of Training and …, 2021 - emerald.com
Purpose As new technologies such as immersive and augmented platforms emerge, training
approaches are also transforming. The virtual reality (VR) platform provides a completely …

Multiclass emotion prediction using heart rate and virtual reality stimuli

AF Bulagang, J Mountstephens, J Teo - Journal of Big Data, 2021 - Springer
Background Emotion prediction is a method that recognizes the human emotion derived
from the subject's psychological data. The problem in question is the limited use of heart rate …

Stress recognition based on multiphysiological data in high-pressure driving VR scene

R Vaitheeshwari, SC Yeh, EHK Wu… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Human stress recognition has been used in a variety of contexts, including stress caused by
work pressures, mental pressures, trauma, and physical sickness. Meanwhile, the issue of …

A shrewd artificial neural network-based hybrid model for pervasive stress detection of students using galvanic skin response and electrocardiogram signals

S Tiwari, S Agarwal - Big Data, 2021 - liebertpub.com
Mental illness issues are a very common health issue in youths and adults across the world.
The usage of real-time data analytics in health care has a great potential to improve and …

[PDF][PDF] Oversampling approach using radius-SMOTE for imbalance electroencephalography datasets

R Wardoyo, IMA Wirawan… - Emerging Science …, 2022 - pdfs.semanticscholar.org
Several studies related to emotion recognition based on Electroencephalogram signals
have been carried out in feature extraction, feature representation, and classification …

Modeling sleep quality depending on objective actigraphic indicators based on machine learning methods

OV Bitkina, J Park, J Kim - … Journal of Environmental Research and Public …, 2022 - mdpi.com
According to data from the World Health Organization and medical research centers, the
frequency and severity of various sleep disorders, including insomnia, are increasing …