Feature Extraction, Feature Selection and Classification from Electrocardiography to Emotions

Electrocardiography (ECG) is one of the most important physiological signals, whose changes can reflect the changes in emotional states in some degree. Raw ECG data were recorded when film clips were used to elicit target emotions (joy and sadness) of multiple subjects. Wavelet transform was applied to accurately detect QRS complex for its advantages on time-frequency localization, in order to extract features from raw ECG signals. A method of feature selection based on Ant Colony System (ACS), using K-nearest neighbor for emotion classification, was introduced to obtain higher recognition rate and effective feature subset.