Analysis of emotional condition based on electrocardiogram signals

Emotion is a mental condition that appears spontaneously based on self-conscious effort and usually followed by physiological changes. Emotion is especially caused by stimulation. The related information with emotional condition by someone is communicated to all body through ECG. Therefore, it is important to conduct a research in analysis of emotion based on the measurement of ECG. Data emotion was categorised according to the stimulation that had been given to the subject by using video and music as long as ECG recorded. ICA method analysis with FastICA algorithm could be developed to obtain emotion feature. Feature classification was based on statistical approach from the independent component with higher of kurtosis value. The proposed method in classification was based on decision tree using Random Forest algorithm. The classification result shows that the emotional recognition based on ECG signals can be well implemented by system. The developed method successfully classifies the emotional condition from ECG signals. The method achieves the accuracy of 92.2% for identification of neutral emotion, 93.9% for negative emotion and 92.1% for positive emotion. The value of ICSI is obtained about 81.2% for neutral conditions, 88.3% for negative emotions and 85.1% for positive emotions, it means that the system is successfully to classify individually and effective for overall.