Affective computing
Context-Sensitive Bayesian Classifiers and Application to Mouse Pressure Pattern Classification
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Automatic prediction of frustration
International Journal of Human-Computer Studies
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Shybot: friend-stranger interaction for children living with autism
CHI '08 Extended Abstracts on Human Factors in Computing Systems
"How do you know that I don't understand?" A look at the future of intelligent tutoring systems
Computers in Human Behavior
Fundamentals of physiological computing
Interacting with Computers
Power to the people: Leveraging human physiological traits to control microprocessor frequency
Proceedings of the 41st annual IEEE/ACM International Symposium on Microarchitecture
Recognizing and Responding to Student Affect
Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction
Sensors Model Student Self Concept in the Classroom
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Affect-aware tutors: recognising and responding to student affect
International Journal of Learning Technology
Biocybernetic loop: from awareness to evolution
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Proceedings of the international conference on Multimedia
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Proceedings of the 16th European Conference on Pattern Languages of Programs
Hi-index | 0.00 |
HandWave is a small, wireless, networked skin conductance sensor for affective computing applications. It is used to detect information related to emotional, cognitive, and physical arousal of mobile users. Many existing affective computing systems make use of sensors that are inflexible and often physically attached to supporting computers. In contrast, HandWave allows an additional degree of flexibility by providing ad-hoc wireless networking capabilities to a wide variety of Bluetooth devices as well as adaptive biosignal amplification. As a consequence, HandWave is used in a variety of affective computing applications such as games, tutoring systems, experimental data collection, and augmented journaling. This paper describes the novel design attributes of this handheld sensor, its development, and various form factors. Future work includes an extension of this approach to other biometric signals of interest to affective computing researchers.