Open AccessKohonen Neural Network Stress Detection Using Only Electrodermal Activity Features
Author(s) -
Ionut-Vlad Bornoiu,
Ovidiu Grigore
Publication year - 2014
Publication title -
advances in electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 23
eISSN - 1844-7600
pISSN - 1582-7445
DOI - 10.4316/aece.2014.03009
Subject(s) - self organizing map , artificial intelligence , artificial neural network , computer science , pattern recognition (psychology) , machine learning
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