Towards Affective Interfaces for Neural Signal Users

Neural signal users are people with complete paralysis operating computer-based equipment through direct braincomputer interface technologies. In this paper, we discuss the importance of utilizing affective information in interfaces for these people, to include both applying user affect and displaying machine affect. Such information can be invaluable in low-level input adaptation (e.g., interpretation of neural signals), as well as in developing proactive predictive interfaces. We will also show how existing prototypes of environmental controls and communications applications could be augmented by inclusion of affective information.