affective computing


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affective computing

Electronically detecting the mood of a computer user via sensors, cameras, keystroke rhythm detection and other physical means. Affective computing implies that the emotional state of the user can be interpreted, and the software can respond accordingly. For example, the application can tailor answers or assistance in areas such as Internet-based therapy and e-learning.
References in periodicals archive ?
Affective computing has traditionally focused on modeling human reactions using multimodal sensor data, but not text.
Rosalind Picard, a co-author on the paper and professor at MIT who leads research in affective computing, says that personalization is especially important in autism therapy: A famous adage is, "If you have met one person, with autism, you have met one person with autism."
I am therefore disappointed how conservative Hawking was in how he communicated, as I am not the only researcher in this emerging field of "affective computing" who could have aided him in communicating through thought alone.
Almost a century later, in 1997, the field of affective computing [2] has been introduced, which aims for computational modeling of the affective states.
"Emotion AI systems and affective computing are allowing everyday objects to detect, analyse, process and respond to people's emotional states and moods to provide better context and a more personalised experience," said Roberta Cozza, research director, Gartner.
"Emotion AI systems and affective computing are allowing everyday objects to detect, analyze, process and respond to people's emotional states and moods to provide better context and a more personalized experience," said Roberta Cozza, research director at Gartner.
[25], affective computing and sentiment analysis are key for the advancement of AI and all the research fields that stem from it.
Hudlicka, "Affective computing for game design," in Proceedings of the 4th International North-American Conference on Intelligent Games and Simulation (Game-On NA '08), pp.
Various important areas are covered here, broadly medical imaging for healthcare, vision systems in healthcare applications, pattern recognition related to healthcare, big data and data mining in healthcare, multimodal integration for healthcare, affective computing, biometrics issues related to healthcare, and action or emotion or behavior analysis/ recognition [2, 3] for healthcare applications, and so forth.
Wearable technology, as a type of affective computing, is mainly used for activity recognition [2, 3] and feeling or affect detection [4, 5].
Silva, "EEG-based subject independent affective computing models," Procedia Computer Science, vol.
I didn't think there was any systematic way of doing this until I came across the term 'affective computing.' Wikipedia defines it as 'the study and development of systems and devices that can recognize, interpret, process, and simulate human affects.' In short, it is the science for detecting different emotions.