Comparison of Electrocardiogram Signals in Men and Women during Creativity with Classification Approaches
Electrocardiogram (ECG) analysis is mostly used as a valuable tool in the evaluation of cognitive tasks. By taking and analyzing measurements in vast quantities, researchers are working toward a better understanding of how human physiological systems work. For the first time, this study investigated the function of the cardiovascular system during creative thinking. In addition, the difference between male/female and normal/creativity states from ECG signals was investigated. Overall, the purpose of this paper was to illustrate the heart working during the creativity, and discover the creative men or women subjects. For these goals, six nonlinear features of the ECG signal were extracted to detect creativity states. During the three tasks of the Torrance Tests of Creative Thinking (TTCT- Figural B), ECG signals were recorded from 52 participants (26 men and 26 women). Then, the proficiency of two kinds of classification approaches was evaluated: Artificial Neural Network (ANN) and Support Vector Machine (SVM). The results indicated the high accuracy rate of discriminations between male/female (96.09%) and normal/creativity states (95.84%) using ANN classifier. Therefore, the proposed method can be useful to detect the creativity states.
Creativity, Artificial Neural Network, Electrocardiogram, Gender, Nonlinear Features, Support Vector Machine