Experience in social affective applications

2010 ◽  
Author(s):  
Paul André ◽  
m.c. schraefel ◽  
Alan Dix ◽  
Ryen W. White
Keyword(s):  
Affective Applications

scholarly journals Brain and Body Emotional Responses: Multimodal Approximation for Valence Classification

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 313 ◽  
Author(s):  
Jennifer Sorinas ◽  
Jose Manuel Ferrández ◽  
Eduardo Fernandez
Keyword(s):  
Emotional Responses ◽  
System Level ◽  
Ecg Signal ◽  
Eeg Signal ◽  
Multimodal Approach ◽  
Men And Women ◽  
Affective Applications ◽  
The Relationship ◽  
Selection Of

In order to develop more precise and functional affective applications, it is necessary to achieve a balance between the psychology and the engineering applied to emotions. Signals from the central and peripheral nervous systems have been used for emotion recognition purposes, however, their operation and the relationship between them remains unknown. In this context, in the present work, we have tried to approach the study of the psychobiology of both systems in order to generate a computational model for the recognition of emotions in the dimension of valence. To this end, the electroencephalography (EEG) signal, electrocardiography (ECG) signal and skin temperature of 24 subjects have been studied. Each methodology has been evaluated individually, finding characteristic patterns of positive and negative emotions in each of them. After feature selection of each methodology, the results of the classification showed that, although the classification of emotions is possible at both central and peripheral levels, the multimodal approach did not improve the results obtained through the EEG alone. In addition, differences have been observed between cerebral and peripheral responses in the processing of emotions by separating the sample by sex; though, the differences between men and women were only notable at the peripheral nervous system level.

scholarly journals The Psychological and Physiological Part of Emotions: Multimodal Approximation for Valence Classification

2019 ◽  
Author(s):  
Jennifer Sorinas ◽  
Jose Manuel Ferrández ◽  
Eduardo Fernandez
Keyword(s):  
Physiological Responses ◽  
Ecg Signal ◽  
Eeg Signal ◽  
Multimodal Approach ◽  
Physiological Level ◽  
Men And Women ◽  
Affective Applications ◽  
The Relationship ◽  
Selection Of

AbstractIn order to develop more precise and functional affective applications, it is necessary to achieve a balance between the psychology and the engineering applied to emotions. Signals from the central and peripheral nervous systems have been used for emotion recognition purposes, however, their operation and the relationship between them remains unknown. In this context, in the present work we have tried to approach the study of the psychobiology of both systems in order to generate a computational model for the recognition of emotions in the dimension of valence. To this end, the electroencephalography (EEG) signal, electrocardiography (ECG) signal and skin temperature of 24 subjects have been studied. Each methodology has been evaluated individually, finding characteristic patterns of positive and negative emotions in each of them. After feature selection of each methodology, the results of the classification showed that, although the classification of emotions is possible at both central and peripheral levels, the multimodal approach did not improve the results obtained through the EEG alone. In addition, differences have been observed between cerebral and physiological responses in the processing emotions by separating the sample by sex; though, the differences between men and women were only notable at the physiological level.

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