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Affective Computing
Open accessAbstract
According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. The latest scientific findings indicate that emotions play an essential role in decision making, perception, learning, and more—that is, they influence the very mechanisms of rational thinking. Not only too much, but too little emotion can impair decision making. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. Part 1 of this book provides the intellectual framework for affective computing. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part 2 discusses the design and construction of affective computers. Although this material is more technical than that in Part 1, the author has kept it less technical than typical scientific publications in order to make it accessible to newcomers. Topics in Part 2 include signal-based representations of emotions, human affect recognition as a pattern recognition and learning problem, recent and ongoing efforts to build models of emotion for synthesizing emotions in computers, and the new application area of affective wearable computers.
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“In contrast, the goal of our system was to use on-body sensors with EDA and electrocardiogram (EKG), since these sensors have been shown to be reliable for emotion detection [14,17,18].”
From Food and Mood: Just-in-Time Support for Emotional Eating (2013) · cites this paper as [18]
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Estrada, J. E., Buhia, J., Guevarra, A., & Forcado, M. R. G. (2018) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-319-98752-1_13 · Cited by 6
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Cunningham, S., Weinel, J., & Picking, R. (2018) · Audio Mostly Conference (AM) · doi:10.1145/3243274.3243313 · Cited by 6
Pimentel, C. F., & Cravo, M. R. (2005) · Lecture notes in computer science · doi:10.1007/11595014_12 · Cited by 6
Halevy, A. Y. (2019) · IEEE Data(base) Engineering Bulletin · Cited by 6
User-oriented requirements engineering
Sutcliffe, A. (2014) · doi:10.1109/usare.2014.6890993 · Cited by 6
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Mainzer, K. (2023) · Springer Reference Geisteswissenschaften · doi:10.1007/978-3-658-23715-8_58-1 · Cited by 6
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Deep Learning Based Emotion Recognition from Chinese Speech
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Picard, R. W., & Cosier, G. (1999) · Springer eBooks · doi:10.1007/978-1-4615-5291-8_13 · Cited by 6
Self-citationDesigning an Emotional Majormodo in Smart Home Healthcare
An, P., Wang, Z., Shi, X., Deng, C., Bian, L., & Chen, L. (2009) · International Asia Symposium on Intelligent Interaction and Affective Computing · doi:10.1109/asia.2009.29 · Cited by 6
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Piwek, P. (2003) · Cited by 6
Simulation of Emotional Processes in Decision Making
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Cosier, G., & Whittaker, S. (2001) · BT Technology Journal · doi:10.1023/a:1013734730842 · Cited by 6
Song, I., & Guido Governatori, A. (2006) · Adaptive Agents and Multi-Agents Systems · doi:10.1145/1160633.1160874 · Cited by 6
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Future Perspectives in Educational Psychology
Miller, G. E., & Reynolds, W. M. (2003) · Handbook of Psychology · doi:10.1002/0471264385.wei0724 · Cited by 6
Toptsis, A. A., & Dubitski, A. (2008) · The Open Artificial Intelligence Journal · Cited by 6
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Bosman, R., & van Winden, F. A. A. M. (1999) · RePEc: Research Papers in Economics · doi:10.2139/ssrn.263347 · Cited by 6
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Broekens, J., Qu, C., & Brinkman, W. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1211.4500 · Cited by 6
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Emotions in Pervasive Computing EnvironmentsPreprint
Jungum, N. V., & Laurent, É. (2009) · arXiv (Cornell University) · doi:10.48550/arxiv.0912.1810 · Cited by 6
A reflexive, not impulsive agent
Pélachaud, C., Poggi, I., DeCarolis, B., & de Rosis, F. (2001) · Adaptive Agents and Multi-Agents Systems · doi:10.1145/375735.376102 · Cited by 6
Emotions as a Bridge to the Environment: On the Role of Body in Organisms and Robots
Pérez, C. H., Moffat, D. C., & Ziemke, T. (2006) · Lecture notes in computer science · doi:10.1007/11840541_1 · Cited by 6
Kushlev, K. (2015) · cIRcle (University of British Columbia) · doi:10.14288/1.0166492 · Cited by 7
User-Centered Revolution: 1995–2008
Nahl, D. (2009) · CRC Press eBooks · doi:10.1081/e-elis3-120044680 · Cited by 6
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Haruvi, A., Kopito, R., Brande-Eilat, N., Kalev, S., Kay, E., & Furman, D. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.02.438269 · Cited by 6
Creature comforts : an exploration of comfort in the home
Burris, A. (2014) · Loughborough University Institutional Repository (Loughborough University) · Cited by 6
Emotions in Advanced Learning Technologies
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McStay, A. (2025) · IEEE Transactions on Technology and Society · doi:10.1109/tts.2025.3573875 · Cited by 5
SEED-MYA: A Novel Myanmar Multimodal Dataset for Enhancing Emotion Recognition
Aung, K. P. P., Yin, H.-L., Ma, T.-F., Zheng, W., & Lu, B. (2025) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2025.3586444 · Cited by 5
Metadata
- Authors
- Picard, R. W.
- Affiliations
- MIT Media Lab (US)
- Corresponding author
- Picard, Rosalind W.
- ORCID
- Picard, Rosalind W.
- Venue
- MIT Press
- Publisher
- The MIT Press
- Published
- 1997-09-24
- OpenAlex
- W2339343773
- Cited by
- 7,382
- References
- 0
- Citations by year
- 2026: 376 · 2025: 295 · 2024: 212 · 2023: 266 · 2022: 208 · 2021: 274 · 2020: 322 · 2019: 356 · 2018: 283 · 2017: 279 · 2016: 301 · 2015: 318 · 2014: 315 · 2013: 335 · 2012: 329
- FWCI
- 92.96
- Type
- book
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-sa
- Locations
- The MIT Press eBooks (publishedVersion)
- PsycEXTRA Dataset (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
- Keywords
- affective computing, emotion recognition, emotion models, emotion synthesis, wearable computers, human-computer interaction, decision-making, pattern recognition
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