Recognizing Stress, Engagement, and Positive Emotion

An intelligent interaction should not typically call attention to emotion. However, it almost always involves emotion: For example, it should engage, not inflict undesirable stress and frustration, and perhaps elicit positive emotions such as joy or delight. How would the system sense or recognize if it was succeeding in these elements of intelligent interaction? This keynote talk will address some ways that our work at the MIT Media Lab has advanced solutions for recognizing user emotion during everyday experiences.

[1]  Rosalind W. Picard,et al.  A Wearable Sensor for Unobtrusive, Long-Term Assessment of Electrodermal Activity , 2010, IEEE Transactions on Biomedical Engineering.

[2]  Henry Lieberman,et al.  Common Sense Reasoning for Detection, Prevention, and Mitigation of Cyberbullying , 2012, TIIS.

[3]  Rosalind W. Picard,et al.  Autonomic changes with seizures correlate with postictal EEG suppression , 2012, Neurology.

[4]  Bilge Mutlu,et al.  MACH: my automated conversation coach , 2013, UbiComp.

[5]  Rosalind W. Picard,et al.  Multiple Arousal Theory and Daily-Life Electrodermal Activity Asymmetry , 2016 .

[6]  Akane Sano,et al.  Recognition of sleep dependent memory consolidation with multi-modal sensor data , 2013, 2013 IEEE International Conference on Body Sensor Networks.

[7]  Javier Hernandez,et al.  Mood meter: counting smiles in the wild , 2012, UbiComp.

[8]  Rosalind W. Picard Emotion Research by the People, for the People , 2010 .

[9]  Daniel McDuff,et al.  Exploring Temporal Patterns in Classifying Frustrated and Delighted Smiles , 2012, IEEE Transactions on Affective Computing.

[10]  Daniel McDuff,et al.  Improvements in Remote Cardiopulmonary Measurement Using a Five Band Digital Camera , 2014, IEEE Transactions on Biomedical Engineering.

[11]  Rosalind W. Picard Future affective technology for autism and emotion communication , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.

[12]  Daniel McDuff,et al.  Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild" , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[13]  Jennifer Healey,et al.  Detecting stress during real-world driving tasks using physiological sensors , 2005, IEEE Transactions on Intelligent Transportation Systems.