ABSTRACT
Augmented cognition seeks to revolutionize human-computer interactions by creating a closed loop between the user and the system, one in which the real-time cognitive state of a user is captured via neuroscienti˜c tools and used to modify or adapt the system to optimize human performance. While the notion of better coupling humans and systems together is not new (Licklider, 1960), advances made during the decade of the brain (1990-1999) provided neurological and physiological science and technology advances that allow for real-time capture and understanding of the human cognitive state using noninvasive means, thereby providing a key component to the realization of augmented cognition systems. The formal research community stemmed from the Defense Advanced Research Projects Agency’s (DARPA’s) Augmented Cognition program*, which was initiated in 2000. This initial research into the ˜eld of augmented cognition focused on identifying and mitigating human limitations in cognitive processes, particularly attention and working memory, which place a ceiling on the capacity of the brain to process and store information with the goal of optimizing human performance. Since that time, great strides in sensor technology, software-based algorithms to classify a variety of human cognitive states in real time, and software design solutions that incorporate dynamic interfaces to support real-time updates to optimize human performance given a variety of states have been made. While such augmented cognition sensors and systems are beginning to emerge on the market (Libelium, 2014; Lomas, 2014), ongoing research continues to stretch the bounds of science and technology as areas of application are beginning to unfold. One area in which augmented cognition could have value is that of evaluating a virtual environment (VE).
