AIMC Topic: Arousal

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Machine Learning Techniques for Arousal Classification from Electrodermal Activity: A Systematic Review.

Sensors (Basel, Switzerland)
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 scientific databases, fifty-nine were finally selected accordi...

Being watched by a humanoid robot and a human: Effects on affect-related psychophysiological responses.

Biological psychology
Eye contact with a humanoid robot has been shown to evoke similar affect and affiliation related psychophysiological responses as eye contact with another human. In this pre-registered study, we investigated whether these effects are dependent on the...

Graph Theoretical Analysis of EEG Functional Connectivity Patterns and Fusion with Physiological Signals for Emotion Recognition.

Sensors (Basel, Switzerland)
Emotion recognition is a key attribute for realizing advances in human-computer interaction, especially when using non-intrusive physiological sensors, such as electroencephalograph (EEG) and electrocardiograph. Although functional connectivity of EE...

CNN-XGBoost fusion-based affective state recognition using EEG spectrogram image analysis.

Scientific reports
Recognizing emotional state of human using brain signal is an active research domain with several open challenges. In this research, we propose a signal spectrogram image based CNN-XGBoost fusion method for recognising three dimensions of emotion, na...

Simultaneously exploring multi-scale and asymmetric EEG features for emotion recognition.

Computers in biology and medicine
In recent years, emotion recognition based on electroencephalography (EEG) has received growing interests in the brain-computer interaction (BCI) field. The neuroscience researches indicate that the left and right brain hemispheres demonstrate activi...

Effect of robot's vertical body movement on its perceived emotion: A preliminary study on vertical oscillation and transition.

PloS one
The emotion expressions of social robots are some of the most important developments in recent studies on human-robot interactions (HRIs). Several research studies have been conducted to assess effective factors to improve the quality of emotion expr...

EEG Feature Extraction and Data Augmentation in Emotion Recognition.

Computational intelligence and neuroscience
Emotion recognition is a challenging problem in Brain-Computer Interaction (BCI). Electroencephalogram (EEG) gives unique information about brain activities that are created due to emotional stimuli. This is one of the most substantial advantages of ...

Two-dimensional CNN-based distinction of human emotions from EEG channels selected by multi-objective evolutionary algorithm.

Scientific reports
In this study we explore how different levels of emotional intensity (Arousal) and pleasantness (Valence) are reflected in electroencephalographic (EEG) signals. We performed the experiments on EEG data of 32 subjects from the DEAP public dataset, wh...

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning.

Nature communications
Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these components have not been reported. Here, we propose an ex...

Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach.

Sensors (Basel, Switzerland)
Extensive possibilities of applications have rendered emotion recognition ineluctable and challenging in the fields of computer science as well as in human-machine interaction and affective computing. Fields that, in turn, are increasingly requiring ...