A continuous and objective evaluation of emotional experience with interactive play environments
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using noninvasive wearable computers to recognize human emotions from physiological signals
EURASIP Journal on Applied Signal Processing
Biometric Responses to Music-Rich Segments in Films: The CDVPlex
CBMI '09 Proceedings of the 2009 Seventh International Workshop on Content-Based Multimedia Indexing
Psycho-physiological measures for assessing cognitive load
Proceedings of the 12th ACM international conference on Ubiquitous computing
Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
IEEE Transactions on Affective Computing
Love, hate, arousal and engagement: exploring audience responses to performing arts
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Out of the lab and into the fray: towards modeling emotion in everyday life
Pervasive'10 Proceedings of the 8th international conference on Pervasive Computing
StressSense: detecting stress in unconstrained acoustic environments using smartphones
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
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The ability to assess fine-scale user responses has applications in advertising, content creation, recommendation, and psychology research. Unfortunately, current approaches, such as focus groups and audience surveys, are limited in size and scope. In this paper, we propose a combined biometric sensing and analysis methodology to leverage audience-scale electro-dermal activity (EDA) data for the purpose of evaluating user responses to video. We provide detailed characterization of how temporal physiological responses to video stimulus can be modeled, along with first-of-its-kind audience-scale EDA group experiments in uncontrolled real-world environments. Our study provides insights into the techniques used to analyze EDA, the effectiveness of the different temporal features, and group dynamics of audiences. Our experiments demonstrate the ability to classify movie ratings with accuracy of over 70% on specific films. Results of this study suggest the ability to assess emotional reactions of groups using minimally invasive sensing modalities in uncontrolled environments.