[HTML][HTML] A systematic survey on multimodal emotion recognition using learning algorithms
Emotion recognition is the process to detect, evaluate, interpret, and respond to people's
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
[HTML][HTML] Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
Comparing recognition performance and robustness of multimodal deep learning models for multimodal emotion recognition
Multimodal signals are powerful for emotion recognition since they can represent emotions
comprehensively. In this article, we compare the recognition performance and robustness of …
comprehensively. In this article, we compare the recognition performance and robustness of …
EEG-based emotion recognition using an end-to-end regional-asymmetric convolutional neural network
Emotion recognition based on electroencephalography (EEG) is of great important in the
field of Human–Computer Interaction (HCI), which has received extensive attention in recent …
field of Human–Computer Interaction (HCI), which has received extensive attention in recent …
Self-supervised ECG representation learning for emotion recognition
We exploit a self-supervised deep multi-task learning framework for electrocardiogram
(ECG)-based emotion recognition. The proposed solution consists of two stages of learning …
(ECG)-based emotion recognition. The proposed solution consists of two stages of learning …
CNN and LSTM based ensemble learning for human emotion recognition using EEG recordings
A Iyer, SS Das, R Teotia, S Maheshwari… - Multimedia Tools and …, 2023 - Springer
Emotion is a significant parameter in daily life and is considered an important factor for
human interactions. The human-machine interactions and their advanced stages like …
human interactions. The human-machine interactions and their advanced stages like …
Multi-channel EEG-based emotion recognition via a multi-level features guided capsule network
In recent years, deep learning (DL) techniques, and in particular convolutional neural
networks (CNNs), have shown great potential in electroencephalograph (EEG)-based …
networks (CNNs), have shown great potential in electroencephalograph (EEG)-based …
[HTML][HTML] Multi-modality approaches for medical support systems: A systematic review of the last decade
Healthcare traditionally relies on single-modality approaches, which limit the information
available for medical decisions. However, advancements in technology and the availability …
available for medical decisions. However, advancements in technology and the availability …
Emotion recognition from EEG based on multi-task learning with capsule network and attention mechanism
Deep learning (DL) technologies have recently shown great potential in emotion recognition
based on electroencephalography (EEG). However, existing DL-based EEG emotion …
based on electroencephalography (EEG). However, existing DL-based EEG emotion …
[HTML][HTML] Emotion detection using electroencephalography signals and a zero-time windowing-based epoch estimation and relevant electrode identification
Recognizing emotions using biological brain signals requires accurate and efficient signal
processing and feature extraction methods. Existing methods use several techniques to …
processing and feature extraction methods. Existing methods use several techniques to …