Basis for the Implementation of an EEG-Based Single-Trial Binary Brain Computer Interface Through the Disgust Produced by Remembering Unpleasant Odors

In order to implement an EEG-based brain computer interface (BCI), a very large number of strategies (ranging from sensory-motor, p300, auditory based, visually based) can be used. However, no technique exists which is based on the olfactory stimulation or, better, based on the imagination of olfactory stimuli.The present paper describes an innovative paradigm, that is the voluntary brain activation with the disgust produced by remembering unpleasant odors, and a simple and robust classification method on which a single trial binary BCI can be implemented. In order to classify the signal, mainly the channels P4, C4, T8 and P8 have been used, by spanning the frequency band between 32 and 42. Hz, that is a subset of the gamma band external to the bands usually occupied by other tasks (the interval between 1 and 30. Hz), and the alpha band between 8 and 12. Hz.Right hemisphere of the brain and gamma band of frequencies are particularly sensitive when experiencing negative emotions, such as the disgust produced by smelling or remembering unpleasant odors, while the alpha band is usually modified with concentration. This constitutes an advantage for the proposed classification technique because it is made intrinsically easy by the localization into particular positions and frequencies: different features are mostly based on different frequency bands.The choice of disgust produced by remembering unpleasant odors is twofold: smelling is an ancestral sensation which is so strong that its EEG signal is produced also in persons affected by hyposmia when they imagine an olfactory situation; it can be used without external stimulation, that is the user can decide freely when and if activate it.The proposed method and the experimental setup are described and a series of experimental measurements are presented and discussed. The accuracy of the proposed method is also evaluated and the reached levels are about 90%. The proposed system can be a useful communication alternative for disabled people that cannot use other BCI paradigms.