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.
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."