Thus, it is possible to speak of "emotion recognition", but this should be interpreted as "measurement of observations of motor behavior that correspond with high probability to an underlying emotion or a combination of emotions". According to Calvo et al ( ) the detection of affective states does not have to be perfect, but must be adapted to the target . Emotion detection is, however, a very challenging problem because emotions are constructs (i.e., conceptual quantities that cannot be directly measured) with fuzzy boundaries and with substantial individual variations in expression and experience.
The detection sensors The sensors can measure different types of signals and can be incorporated into devices such as PCs, smartphones, smartwatches or wearables. To date, significant work has been done on emotion recognition using audio (speech and voice), visual (facial expressions) , an wedding photo editing service motion (body posture and gestures) data. Furthermore, in recent years, many wearable devices are equipped with a range of sensors capable of monitoring physiological signals, including multimodal ones (e.g. heart rate, galvanic skin response, etc.) for emotion recognition. In general, emotion recognition methods could be classified into two main groups.
Those that measure the body's internal signals corresponding to physiological indices, such as electroencephalogram (EEG), temperature (T), electrocardiogram (ECG), electromyography (EMG), galvanic skin response (GSR) and respiration (RSP), electrooculography (EOG), heart rate and its variations and respiratory rate. These parameters are more reliable as they are difficult for the subject to control Those that measure external signals , i.e. human physical signals, also called audiovisual, such as facial expression, speech (both at a semantic and acoustic level), gestural communication, posture, eye movement. These have been studied for years and have the advantage of being easily detected. However, reliability cannot be guaranteed, as it is relatively easy for people to control physical cues such as facial expression or speech to hide their real emotions, especially during social communications In both cases, from a theoretical point of view.