[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 …
A survey on physiological signal-based emotion recognition
Physiological signals are the most reliable form of signals for emotion recognition, as they
cannot be controlled deliberately by the subject. Existing review papers on emotion …
cannot be controlled deliberately by the subject. Existing review papers on emotion …
EEG-based detection of emotional valence towards a reproducible measurement of emotions
A methodological contribution to a reproducible Measurement of Emotions for an EEG-
based system is proposed. Emotional Valence detection is the suggested use case. Valence …
based system is proposed. Emotional Valence detection is the suggested use case. Valence …
A survey on EEG-based solutions for emotion recognition with a low number of channels
The market uptake of Brain-Computer Interface technologies for clinical and non-clinical
applications is attracting the scientific world towards the development of daily-life wearable …
applications is attracting the scientific world towards the development of daily-life wearable …
Applying self-supervised representation learning for emotion recognition using physiological signals
KG Montero Quispe, DMS Utyiama, EM Dos Santos… - Sensors, 2022 - mdpi.com
The use of machine learning (ML) techniques in affective computing applications focuses on
improving the user experience in emotion recognition. The collection of input data (eg …
improving the user experience in emotion recognition. The collection of input data (eg …
Application of fractional Fourier transform in feature extraction from ELECTROCARDIOGRAM and GALVANIC SKIN RESPONSE for emotion recognition
F Panahi, S Rashidi, A Sheikhani - Biomedical Signal Processing and …, 2021 - Elsevier
Emotion recognition from physiological signals plays an essential role in human–computer
interaction and affective computing. This paper aims to study the effectiveness of Fractional …
interaction and affective computing. This paper aims to study the effectiveness of Fractional …
Attention based hybrid deep learning model for wearable based stress recognition
Stress recognition is the process of identifying and assessing an individual's physiological
and psychological responses to stressors, which has significant implications for human well …
and psychological responses to stressors, which has significant implications for human well …
[HTML][HTML] Wearable electroencephalography and multi-modal mental state classification: A systematic literature review
Background: Wearable multi-modal time-series classification applications outperform their
best uni-modal counterparts and hold great promise. A modality that directly measures …
best uni-modal counterparts and hold great promise. A modality that directly measures …
Automatic classification of emotions based on cardiac signals: a systematic literature review
Emotions play a pivotal role in human cognition, exerting influence across diverse domains
of individuals' lives. The widespread adoption of artificial intelligence and machine learning …
of individuals' lives. The widespread adoption of artificial intelligence and machine learning …
Hardware acceleration of EEG-based emotion classification systems: a comprehensive survey
Recent years have witnessed a growing interest in EEG-based wearable classifiers of
emotions, which could enable the real-time monitoring of patients suffering from …
emotions, which could enable the real-time monitoring of patients suffering from …