The field of Physiological Computing consists of systems that use data from the human nervous system as control input to a technological system. Traditionally these systems have been grouped into two categories, those where physiological data is used as a form of input control and a second where spontaneous changes in physiology are used to monitor the psychological state of the user. The field of Brain-Computer Interfacing (BCI) traditionally conceives of BCIs as a controller for interfaces, a device which allows you to “act on” external devices as a form of input control. However, most BCIs do not provide a reliable and efficient means of input control and are difficult to learn and use relative to other available modes. We propose to change the conceptual use of “BCI as an actor” (input control) into “BCI as an intelligent sensor” (monitor). This shift of emphasis promotes the capacity of BCI to represent spontaneous changes in the state of the user in order to induce intelligent adaptation at the interface. BCIs can be increasingly used as intelligent sensors which “read” passive signals from the nervous system and infer user states to adapt human-computer, human-robot or human-human interaction (HCI, HRI, HHI). This perspective on BCIs challenges researchers to understand how information about the user state should support different types of interaction dynamics, from supporting the goals and needs of the user to conveying state information to other users. What adaptation to which user state constitutes opportune support? How does the feedback of the changing HCI and human-robot interaction affect brain signals? Many research challenges need to be tackled here.

• http://hmi.ewi.utwente.nl/BCIGrandChallenge2012/

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