Toward Machine Emotional Intelligence: Analysis of Affective Physiological State
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Toward a decision-theoretic framework for affect recognition and user assistance
International Journal of Human-Computer Studies - Human-computer interaction research in the managemant information systems discipline
Learning Bayesian Networks
Emotion Recognition Based on Physiological Changes in Music Listening
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automated stress detection using keystroke and linguistic features: An exploratory study
International Journal of Human-Computer Studies
Artificial Intelligence in Medicine
Affectively intelligent and adaptive car interfaces
Information Sciences: an International Journal
IEEE Transactions on Affective Computing
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
ECG Pattern Analysis for Emotion Detection
IEEE Transactions on Affective Computing
Detecting stress during real-world driving tasks using physiological sensors
IEEE Transactions on Intelligent Transportation Systems
Detecting cocaine use with wearable electrocardiogram sensors
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Modeling stress recognition in typical virtual environments
Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare
Sensor-less sensing for affective computing and stress management technology
Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare
Applied Soft Computing
Modeling observer stress for typical real environments
Expert Systems with Applications: An International Journal
Journal of Ambient Intelligence and Smart Environments
Journal of Ambient Intelligence and Smart Environments - Context Awareness
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With advances in physiological sensors, we are able to understand people's physiological status and recognize stress to provide beneficial services. Despite the great potential in physiological stress recognition, there are some critical issues that need to be addressed such as the sensitivity and variability of physiology to many factors other than stress (e.g., physical activity). To resolve these issues, in this paper, we focus on the understanding of physiological responses to both stressor and physical activity and perform stress recognition, particularly in situations having multiple stimuli: physical activity and stressors. We construct stress models that correspond to individual situations, and we validate our stress modeling in the presence of physical activity. Analysis of our experiments provides an understanding on how physiological responses change with different stressors and how physical activity confounds stress recognition with physiological responses. In both objective and subjective settings, the accuracy of stress recognition drops by more than 14% when physical activity is performed. However, by modularizing stress models with respect to physical activity, we can recognize stress with accuracies of 82% (objective stress) and 87% (subjective stress), achieving more than a 5-10% improvement from approaches that do not take physical activity into account.