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Kohonen Neural Network Stress Detection Using Only Electrodermal Activity FeaturesBORNOIU, I.-V. , GRIGORE, O.
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biomedical signal processing, data analysis, electrophysiology, pattern recognition, self organizing feature maps
stress(7), electrodermal(6), activity(5), emotion(4)
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About this article
Date of Publication: 2014-08-31
Volume 14, Issue 3, Year 2014, On page(s): 71 - 78
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.03009
Web of Science Accession Number: 000340869800009
SCOPUS ID: 84907310113
This paper presents a method for identifying human stress levels by using a Kohonen neural network. The study focuses on differentiating between a relaxed and a stressed state and it presents a series of parameters (skin conductance response signal power, skin conductance response signal frequency, skin conductance level gradient, response rise time and response amplitude) extracted only from the electrodermal activity signal. A very strict recording protocol was used to minimize the artifacts caused by the bad connection between electrodes and skin. A stress inducing method is presented that can be used to replicate results in laboratory conditions.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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