سال انتشار: ۱۳۹۳
محل انتشار: دومین کنفرانس بین المللی دستاوردهای نوین در علوم مهندسی و پایه
تعداد صفحات: ۵
نویسنده(ها):
Sahae Zakeri – M.Sc. Student, Computational Neuroscience Laboratory, Department of Biomedical Engineering, Faculty ofElectrical Engineering, Sahand University of Technology, Tabriz, Iran
Ataollah Abbasi – Assistant professor, Computational Neuroscience Laboratory, Department of Biomedical Engineering, Faculty ofElectrical Engineering, Sahand University of Technology, Tabriz, Iran
Ateke Goshvarpour – Ph.D. Student, Computational Neuroscience Laboratory, Department of Biomedical Engineering, Faculty ofElectrical Engineering, Sahand University of Technology, Tabriz, Iran

چکیده:

As Electrocardiogram (ECG) analysis is often used to detect cognitive behavior, this paper presents anovel approach for distinction between male/female and normal/creativity states from ECG signals. The goal of thisarticle is to indicate the heart mechanisms that mediate creativity, and how detect the creative men or womensubjects. For these purposes, a nonlinear feature of the ECG signal was extracted to detect creativity states. Doingthree tasks of Torrance Tests of Creative Thinking (TTCT- Figural B), ECG signals of 52 participants (26 men, 26women and 19-24 years) were recorded. Then, the performance of Support Vector Machine (SVM) classificationwas evaluated. The results showed that the best accuracy between male/female is 91.74% and normal/creativitystates is 91.36% with this classifier.