# Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals
## 3 Research and Application of EDA, ECG and EMG  
EDA, used to describe variations in the conductivity of skin, measures the electrical features of skin through skin conductance response, skin potential, skin conductance level or skin potential response. EDA is mature and non-invasive and has many advantages such as reliability, user-friendly acquisition, swift response, and low cost; hence, it is used to study many issues. [PERSON] et al. [45] identified specific stress regions in the valence-arousal space by combining pairs of valence-arousal and skin conductance for 31 volunteers. The findings showed which regions in the valence-arousal rating space could express self-reported stress in accordance with the subject's skin conductance. They also presented a new method for the empirical discrimination of emotion regions in the valence-arousal space. [PERSON] et al. [46] proposed an automated method of classifying emotions for children using EDA. The results quantitatively indicated that the proposed method could significantly improve emotion classification using wavelet-based features. [PERSON] [47] selected songs with the most increased or decreased skin conductance levels in 10 subjects to cause an energetic or calm motion based on the resulting user models. The results indicated that the effect of a song on skin conductance could be reliably predicted, and skin conductance that could kept in certain state for at least 30 min was directly related to energetic or calm mood. It was feasible to reflect the emotional response of listeners through physiological signals. [PERSON] et al. [48] studied the application of data gloves with two systems: one was a system of emotion recognition and judgment that was built based on the optimal features of EDA, and another was a system of virtual gesture control and a manipulator propelled by emotion, as shown in Figure 1. The test results for five subjects showed that the system could regulate the gestures of a virtual hand through reading the signals of skin electricity when the subjects did not change any gesture, and the manipulator could complete the steering change driven by emotion as shown in Figure 2, where the bottom row is the duration of the music, the middle row is the EDA signals of subjects after listening to music, and the top row is the manipulator steering change driven by emotion based on the EDA signals. [PERSON] et al. [49] studied the differences in people's assessments of tactile sensations for beech surfaces of different shapes and roughness using skin conductance and subjective emotion measurement of pleasure arousal dominance. They found that, under a relatively high level of emotional arousal, the subject's emotional stability could be partly retained because of a beech with arc shapes. As for perception of beech, males had a larger range of emotional arousal and lower speed of emotional arousal than females. [PERSON] et al. [50] combined people's individual EDA features and music features, and presented a network of residual temporal and channel attention. They first applied a mechanism of channel-temporal attention for EDA-based emotion recognition to explore dynamic and steady temporal and channel-wise features and proved the effectiveness of the presented network for mining EDA features. [PERSON] et al. [51] developed a tool and presented a set to complement psychological data based on EDA, and a comparison of accuracy of the k-means classification with the independent division revealed the best results for negative emotions (78.05%). The comparison of the division of the participants according to the classifier is shown in Table 3, where JAWS is Job-related Affective Well-being Scale, \"pos\" is positive, \"neg\" is negative, PCA is partial component analysis, ACC is accuracy. ECG measures a physiological signal generated from the contraction and recovery of the heart, and ECG technology uses an electrocardiograph to record the electrical activity changes of the heart from the body surface in each cardiac cycle.