Mental Stress Detection Using Physiological Signals Based on Soft Computing Techniques
Publish place: 18th Iranian conference on Biomedical Engineering
Publish Year: 1390
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICBME18_008
تاریخ نمایه سازی: 27 فروردین 1393
Abstract:
This paper presents a novel approach for mentalstress detection. In proposed system, three signals includingPupil Diameter (PD), Electrocardiogram (ECG) andPhotoplethysmogram (PPG) are analyzed using the softcomputing techniques, and most relevant features are extractedfrom each one. Then, the optimized features are selected byusing the Genetic Algorithm (GA) and imported into the FuzzySVM (FSVM) to classify stress” and relaxation” states. Inorder to evaluate the performance of proposed system, amultimodal dataset consisting of pupil video, ECG and PPGsignals are constructed; a Stroop color-word (SCW) test isdesigned to act as the stimulus to induce stress in healthysubjects. The experimental results demonstrate thephysiological signals have great potential for stress detection,and the proposed system provides high classificationperformance.
Authors
F Mokhayeri
Department of Biomedical Engineering, Islamic Azad University, Mashhad Branch, Mashhad, Iran
M-R Akbarzadeh-T
Departments of Electrical Engineering and Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
S Toosizadeh
Department of Electrical Engineering, Islamic Azad University, Mashhad Branch, Mashhad, Iran