Use of sympathetic skin response along with artificial neural networks in diagnosing of fibromyalgia syndrome

Biomedical signals are important data used for diagnosing of diseases because of containing important information about body functions. Artificial neural network (ANN) is one of the most important methods used for analyzing and evaluating the biomedical signals.In this thesis, a new diagnostic method for fibromyalgia syndrome (FMS) which is a muscu-skeletal disease, especially common in women, affecting the autonomic nervous system is proposed. In this context, the results of diagnosis of the disease were obtained and they were used as a database in this thesis. Then sympathetic skin response (SSR) is one of biomedical signal obtained from the human body was measured from the same subjects and recorded to the database. The parameters related to the disease were extracted from the SSR waves and the numerical values of these parameters calculated by Matlab software and were recorded to the database.In the thesis, SSR parameter values and psychological test scores which depend on the patient's asked questions and used in the diagnosis of the disease were analyzed by ANN and the diagnostic accuracy percentages were calculated. Then, the laboratory test results and the SSR parameter values belong to the subjects were analyzed separately and together by using ANN. The effect of the SSR parameters to the laboratory tests is investigated by considering the results of the ANN analysis and calculated diagnostic accuracy percentages. In the last part of the thesis, laboratory test results, physiological test scores and SSR parameter values belong to the subjects were analyzed by using ANN separately and together, diagnostic accuracy percentages were calculated for each condition, thus, the effect of the SSR parameters to the diagnosis methods of fibromyalgia syndrome is investigated.Evaluating the calculated diagnostic accuracy percentages by using ANN, it was concluded that selected parameters of the SSR supported to the results obtained from the tests used in diagnosis of FMS and SSR signals must be taken into consideration for diagnosing of the disease.