DocumentCode
3582646
Title
Stress detection of computer user in office like working environment using neural network
Author
Abu Baker Siddique Akhonda, Md ; Md Foorkanul Islam, Shaon ; Shehab Khan, Ahmed ; Ahmed, Fariha ; Mostafizur Rahman, Md
Author_Institution
Dept. of Electron. & Commun. Eng., Khulna Univ. of Eng. & Technol., Khulna, Bangladesh
fYear
2014
Firstpage
174
Lastpage
179
Abstract
Detecting the stress of computer user in an office like environment will enable more development of computer and make it intelligent enough where it can interact with its user, taking users effective state in to account; known as affective computing. In this research work, we have analyzed physical and mental stress of a computer user in all day long working environment by analyzing variations in physiological signals. Physiological data sets of 12 subjects were collected where all the subjects were went through a specific sequence of computer using session which includes different computer mediated task. To determine the stress level accurately and for detailed analysis of stress condition a three layer back propagation (BP) neural network were constructed. Research shows that stress level of a subject varies with computer using time and subject´s effort towards work. And induced stress is mainly due to intense eye work and mental strain.
Keywords
backpropagation; electro-oculography; electrocardiography; electromyography; human factors; medical signal processing; neural nets; neurophysiology; occupational stress; BP neural network; ECG signal; EMG signal; EOG signal; Physiological data sets; affective computing; computer mediated task; computer sequence; computer user stress detection; computer using time; induced stress; intense eye work; mental stress analysis; office-like working environment; physical stress analysis; physiological signal variation analysis; stress condition; three-layer backpropagation neural network; user effective state; user work effort; Computers; Electroencephalography; Electromyography; Electrooculography; Feature extraction; Stress; Time-frequency analysis; Affective computing; Artificial Neural Network; BP; physiological signal; stress detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Technology (ICCIT), 2014 17th International Conference on
Type
conf
DOI
10.1109/ICCITechn.2014.7073120
Filename
7073120
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