Kohonen Neural Network Stress Detection Using Only Electrodermal Activity Features

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,...

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Bibliographic Details
Published in:Advances in electrical and computer engineering 2014-01, Vol.14 (3), p.71-78
Main Authors: BORNOIU, I.-V., GRIGORE, O.
Format: Article
Language:English
Subjects:
Amplitudes
biomedical signal processing
Conductance
data analysis
Electric power generation
Electrodes
electrophysiology
Human
Neural networks
pattern recognition
Recording
self organizing feature maps
Stresses
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Summary: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.
ISSN:1582-7445
1844-7600
DOI:10.4316/AECE.2014.03009