Affective computing is human-computer interaction in which a device has the ability to detect and appropriately respond to its user's emotions and other stimuli. A computing device with this capacity could gather cues to user emotion from a variety of sources. Facial expressions, posture, gestures, speech, the force or rhythm of key strokes and the temperature changes of the hand on a mouse can all signify changes in the user's emotional state, and these can all be detected and interpreted by a computer. A built-in camera captures images of the user and algorithm s are used to process the data to yield meaningful information. Speech recognition and gesture recognition are among the other technologies being explored for affective computing applications.
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Affective computing could offer benefits in an almost limitless range of applications. For example, in e-learning situations, the computer could detect from available cues when the user was having difficulty and offer expanded explanations or additional information. Other applications include e-therapy: psychological health services, such as counseling, delivered online. Internet-based therapy, although increasingly common, does not give a therapist as many cues to the client's emotional state as are available in a real-world session. Through affective computing, the client's posture, gestures, and facial expressions could be used, along with their words, for a more accurate evaluation of their psychological state.
Affective computing gets its name from the field of Psychology, in which "affect" is, basically, a synonym for "emotion."