Authors:
Daniela Iacoviello
1
;
Naixia Pagnani
2
;
Andrea Petracca
2
;
Matteo Spezialetti
2
and
Giuseppe Placidi
2
Affiliations:
1
Sapienza University of Rome, Italy
;
2
University of ĽAquila, Italy
Keyword(s):
Brain Computer Interface, Classification, Emotions, Disgust, Pleasantness, Olfactory Memory.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Instruments and Devices
;
Brain-Computer Interfaces
;
Devices
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Neural Signal Processing
;
NeuroSensing and Diagnosis
;
Neurotechnology, Electronics and Informatics
;
Physiological Computing Systems
Abstract:
Affective Computing and Brain Computer Interface (BCI) are two innovative and rapidly growing fields of research. Affective Computing aims at equipping machines with the human capabilities of observe, understand and express affecting features; BCI aims at discovering novel communication channels and protocols, through the monitoring of the brain activity. Emotion recognition plays a central role in both these research fields. In this work we present an EEG poll based classification algorithm for self-induced emotional states used for BCI. We tested the approach using three emotions: the disgust produced by remembering an unpleasant odor (a stink), the pleasantness induced by the memory of a fragrance and a relaxing state. Preliminary experimental results are also reported.