Citation

Sayeed, Md. Shohel and Mand, Ali Afzalian and Hossen, Md. Jakir and Kassim, Amelia and Pa, Pa Min (2022) Stress Detection using Adaptive Neuro Fuzzy Inference System. Journal of Engineering Science and Technology Review, 15 (5). pp. 70-76. ISSN 1791-9320

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Abstract

A job interview can be challenging and stressful even when one has gone through it many times. Failure to handle the stress may lead to unsuccessful delivery of their best throughout the interview session. Therefore, an alternative method which is preparing a video resume and interview before the actual interview could reduce the level of stress. An intelligent stress detection is proposed to classify individuals with different stress levels by understanding the physiological signal through Electrocardiogram (ECG). The main purpose of this paper is to apply the adaptive neuro fuzzy inference system (ANFIS) on the stress-level detection from Video Interview dataset of 10 male subjects who were recording the video resume for the analysis purposes. The proposed method able to achieve an accuracy of 100 % with the re-clustering and ANFIS framework

Item Type:	Article
Uncontrolled Keywords:	ECG, ANFIS, Stress Detection, Re-clustering
Subjects:	Q Science > QP Physiology > QP1-345 General Including influence of the environment R Medicine > RC Internal medicine
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	28 Mar 2023 06:58
Last Modified:	28 Mar 2023 06:58
URII:	http://shdl.mmu.edu.my/id/eprint/11279

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