Biocybernetic systems are physiological software systems that explicitly utilize physiological signals to control or adapt software functionality (Pope et al., 1995.) These systems have tremendous potential for innovation in human computer interaction by using physiological signals to infer a user's emotional and mental states (Allanson & Fairclough, 2004; Fairclough, 2008). Nevertheless, development of these systems has been ultimately hindered by two fundamental challenges. First, these systems make generalizations about physiological indicators of cognitive states across populations when, in fact, relationships between physiological responses and cognitive states are specific to each individual (Andreassi, 2006). Second, they often employ largely inconsistent retrospective techniques to subjectively infer user's mental state (Fairclough, 2008).

An individualized biocybernetic system was developed to address the fundamental challenges of biocybernetic research. This system was used to adapt video game difficulty through real-time classifications of physiological responses to subjective appraisals. A study was conducted to determine the system's ability to improve player's performance. The results provide evidence of significant task performance increase and higher attained task difficulty when players interacted with the game using the system than without. This work offers researchers with an alternative method for software adaptation by conforming to the individual characteristics of each user.