Emotion recognition for everyday life using physiological signals from wearables: A systematic literature review

S Saganowski, B Perz, AG Polak… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Smart wearables, equipped with sensors monitoring physiological parameters, are
becoming an integral part of our life. In this work, we investigate the possibility of utilizing …

Virtual reality for emotion elicitation–a review

R Somarathna, T Bednarz… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Emotions are multifaceted phenomena that affect our behaviour, perception, and cognition.
Increasing evidence indicates that induction mechanisms play a crucial role in triggering …

Affective image content analysis: Two decades review and new perspectives

S Zhao, X Yao, J Yang, G Jia, G Ding… - … on Pattern Analysis …, 2021 - ieeexplore.ieee.org
Images can convey rich semantics and induce various emotions in viewers. Recently, with
the rapid advancement of emotional intelligence and the explosive growth of visual data …

A deep-learning model for subject-independent human emotion recognition using electrodermal activity sensors

F Al Machot, A Elmachot, M Ali, E Al Machot… - Sensors, 2019 - mdpi.com
One of the main objectives of Active and Assisted Living (AAL) environments is to ensure
that elderly and/or disabled people perform/live well in their immediate environments; this …

A survey on databases for multimodal emotion recognition and an introduction to the VIRI (visible and InfraRed image) database

MFH Siddiqui, P Dhakal, X Yang, AY Javaid - Multimodal Technologies …, 2022 - mdpi.com
Multimodal human–computer interaction (HCI) systems pledge a more human–human-like
interaction between machines and humans. Their prowess in emanating an unambiguous …

A bayesian deep learning framework for end-to-end prediction of emotion from heartbeat

R Harper, J Southern - IEEE transactions on affective …, 2020 - ieeexplore.ieee.org
Automatic prediction of emotion promises to revolutionise human-computer interaction.
Recent trends involve fusion of multiple data modalities audio, visual, and physiological to …

Hierarchical extreme puzzle learning machine-based emotion recognition using multimodal physiological signals

A Pradhan, S Srivastava - Biomedical Signal Processing and Control, 2023 - Elsevier
Detection of exact emotions through multi-modal physiological signals provides relevant
information for different processes. Numerous computational approaches have been …

A multimodal facial emotion recognition framework through the fusion of speech with visible and infrared images

MFH Siddiqui, AY Javaid - Multimodal Technologies and Interaction, 2020 - mdpi.com
The exigency of emotion recognition is pushing the envelope for meticulous strategies of
discerning actual emotions through the use of superior multimodal techniques. This work …

Personalized Deep Bi-LSTM RNN based model for pain intensity classification using EDA signal

F Pouromran, Y Lin, S Kamarthi - Sensors, 2022 - mdpi.com
Automatic pain intensity assessment from physiological signals has become an appealing
approach, but it remains a largely unexplored research topic. Most studies have used …

Recognition of emotion intensities using machine learning algorithms: A comparative study

D Mehta, MFH Siddiqui, AY Javaid - Sensors, 2019 - mdpi.com
Over the past two decades, automatic facial emotion recognition has received enormous
attention. This is due to the increase in the need for behavioral biometric systems and …