A brain computer interface by EEG signals from self-induced emotions

Human computer interface (HCI) has become more and more important in the last few years. This is mainly due to the increase in the technology and in the new possibilities in yielding a help to disabled people. Brain Computer Interfaces (BCI) represent a subset of the HCI systems which use measurements of the voluntary brain activity for driving a communication system mainly useful for severely disabled people. Electroencephalography (EEG) has been intensively used for the measurement of electrical signals related to the brain activity. The BCI usage requires the activation of mental tasks that could be derived by external stimulations (often audio-visual) or by autonomous activations (for example by thinking to move an arm for signaling a binary command). In the last few years, a new paradigm of activation has been used, consisting in the autonomous brain activation through self-induced emotions, remembered on autobiographical basis. In the present paper, we describe the state of the art of a BCI system based on self-induced emotions, from the activation paradigm to the used signal classification strategies and the final graphic interface. Moreover, we will discuss its extension