Exploring the potential of neurophysiological measures for user-adaptive visualization
S. Tak, Anne-Marie Brouwer, Alexander Toet, Jan B. F. van Erp · TNO Repository · 2013
Abstract. User-adaptive visualization aims to adapt visualized information to the needs and characteristics of the individual user. Current approaches deploy user personality factors, user behavior and preferences, and visual scanning behavior to achieve this goal. We argue that neurophysiological data provide valuable additional input for useradaptive visualization systems since they contain a wealth of objective information about user characteristics. The combination of neurophysiological data with other information like eye movement data can significantly improve system reliability by reducing the inherent uncertainty in the interpretation of the user data. Moreover, neurophysiological data can be obtained continuously and unobtrusively without disturbing the interaction of the user with the system.