With an increase in the number of machines in daily life, there is a need for more intuitive systems that can interpret explicit as well as implicit, more subtle, means of communication. Since emotions and affective expressions play a role in decision-making, learning, and other cognitive functions, human interaction with technology, such as a computer or robot, will improve if affect recognition is part of that interaction. The design of affect-sensitive interactions between humans and technology, a research area known as affective computing, is an increasingly important discipline in the human-robot interaction community. This BRIGE proposal seeks to monitor physiological signals during interactive activities. This project will develop and test wireless, wearable sensors for use in an affect-sensitive adaptive system. The proposed system will make predictions about user's affective states and adapt the interaction to alter and improve user experience. Settings to be examined include games of varying difficulty utilizing an embodied robot and activities focused on teenagers with and without autism during periods of waiting (a likely stress-inducing activity for which external interceding feedback may help autistic individuals cope). The proposed system will allow the interaction to make alterations based on physiological data and inferred affective states to improve human-robot interaction and address social stressors. Broader Impacts: The low-cost and highly deployable technologies developed in this proposal could have significant impact on making physiological signal monitoring more widely available. The results will support the investigation of closed-loop human-robot interaction tasks where the robot will implicitly sense human affective (i.e., emotional) states using affect recognition algorithms, and the robot can then alter its behavior to address specific human needs. They may also create completely new intervention strategies for children with autism. In addition, the educational and broadening participation objectives will engage high school, undergraduate, and graduate students in the design and research evaluation of advanced technologies for autism intervention, human-robot interaction, and affective computing. Efforts to reach out to underrepresented students cover two annual events that will showcase the ongoing research, and the planned experiments allow individuals with disabilities to engage in scientific research. The proposed work has potential to appeal to a wide range of students from electrical engineering, computer engineering, and bioengineering as well as experimental psychology and psychiatry; and findings in this area will address unanswered questions about affective computing.