Measuring the Sympathetic Skin Response on Body and Using as Diagnosis-Purposed for Lung Cancer Patients by Artificial Neural Networks

In this study, the points of Sympathetic skin response that can be measured from different zones on body of healthy and patient subjects are determined. The Sympathetic skin responses on these points are obtained using a measurement device that is called Grass Model 7 Polygraph 1. The database is fo...

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Bibliographic Details
Published in:Journal of medical systems 2010-06, Vol.34 (3), p.407-412
Main Authors: Özkan, Özhan, Yildiz, Murat, Bilgin, Süleyman, Köklükaya, Etem
Format: Article
Language:English
Subjects:
Adolescent
Adult
Algorithms
Body Height - physiology
Body Weight - physiology
Case-Control Studies
Computer Simulation
Electrodiagnosis - methods
Health Informatics
Health Sciences
Humans
Lung cancer
Lung Neoplasms - physiopathology
Measurement techniques
Medical diagnosis
Medicine
Medicine & Public Health
Middle Aged
Neural networks
Neural Networks (Computer)
Original Paper
Peripheral Nervous System Diseases - complications
Peripheral Nervous System Diseases - diagnosis
Skin
Skin Physiological Phenomena
Statistics for Life Sciences
Sweat Glands - innervation
Sympathetic Nervous System - physiology
Sympathetic Nervous System - physiopathology
Young Adult
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Summary:In this study, the points of Sympathetic skin response that can be measured from different zones on body of healthy and patient subjects are determined. The Sympathetic skin responses on these points are obtained using a measurement device that is called Grass Model 7 Polygraph 1. The database is formed in Cerrahpaşa University, Faculty of Medicine and data is taken from healthy and patient subjects who are volunteer. Some parameters of the subjects which are more effective on SSR such as height, weight, age must be chosen between the specific limits to obtain results more clearly. The symmetric points on human body are chosen for the measurement. After that, the Sympathetic skin response values which are measured from a human body are simulated and tested by using artificial neural network toolbox on Matlab software. The structure of the chosen neural network is a multilayer feedforward neural network. According to simulation results, the application method as diagnosis-purposed of the lung cancer patients is explained by using the differences related to these values on the skin.
ISSN:0148-5598
1573-689X
DOI:10.1007/s10916-009-9253-1