EMOTION RECOGNITION IN HUMAN BEINGS BY USING ECG SIGNALS AND HILBERT-HUANG TRANSFORM (Global Journal of Advanced Engineering Technologies and Sciences, 2014)
Emotion is repeatedly defined as a difficult state of feeling that results in substantial and psychological changes that influence thought and behavior. Emotion modeling and detection has drawn wide attention from disciplines such as psychology, cognitive science and engineering. The purpose of this planned work is to recognize the emotional states of human body using ECG signals, which could transform applications in medicine, entertainment, education, safety etc. A solution based on empirical mode decomposition (EMD) is projected for the discovery of dynamically evolving emotion patterns on ECG. Cataloging features are based on the immediate frequency and the local oscillation within every mode. The proposed system uses the fast Fourier transform to remove the noise from the synthetic generated ECG signal and therefore the emotional states were identified efficiently