Machine learning techniques for arousal classification from electrodermal activity: A systematic review

R Sánchez-Reolid, F López de la Rosa… - Sensors, 2022 - mdpi.com
This article introduces a systematic review on arousal classification based on electrodermal
activity (EDA) and machine learning (ML). From a first set of 284 articles searched for in six …

EEG-based emotion recognition with deep convolutional neural networks

MA Ozdemir, M Degirmenci, E Izci… - Biomedical Engineering …, 2021 - degruyter.com
The emotional state of people plays a key role in physiological and behavioral human
interaction. Emotional state analysis entails many fields such as neuroscience, cognitive …

Machine learning for stress detection from electrodermal activity: A scoping review

Early detection of stress can prevent us from suffering from a long-term illness such as
depression and anxiety. This article presents a scoping review of stress detection based on …

Data-driven Modelling of Cognitive and Affective Variables of Perception of Multimedia Content

R Faúndez-Carrasco Población - 2023 - oa.upm.es
Understanding how external stimuli are transformed into meaningful impressions that guide
human actions has been an enduring challenge. Automatic models of perception of …

Predicting group-level skin attention to short movies from audio-based LSTM-mixture of experts models

Electrodermal activity (EDA) is a psychophysiological indicator that can be considered a
somatic marker of the emotional and attentional reaction of subjects towards stimuli like …

Project CAVIAR CApturing VIewers' Affective Response

F Fernández-Martínez, Z Callejas… - … del Lenguaje Natural, 2019 - journal.sepln.org
In this project we propose the automatic analysis of the relation between the audiovisual
characteristics of a multimedia production and the impact caused in its audience. With this …