Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
The roots of backpropagation: from ordered derivatives to neural networks and political forecasting
The roots of backpropagation: from ordered derivatives to neural networks and political forecasting
GSR and HRV: its application in clinical diagnosis
CBMS'03 Proceedings of the 16th IEEE conference on Computer-based medical systems
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Fibromyalgia syndrome (FMS) is a chronic musculoskeletal disease which causes dysfunction of the autonomic nervous system. Sympathetic Skin Response (SSR) is a part of electrical impedance of body which is affected by the autonomic nervous system dysfunctions. In this study, values obtained from the results of the patients diagnosed with fibromyalgia syndrome, and healthy subjects blood samples in the laboratory conditions are recorded in Suleyman Demirel University, Faculty of Medicine, Department of Physical Medicine and Rehabilitation. SSR measurements are recorded from patients and healthy controls. Values of latency time, maximum amplitude and elapsed time between two stimulus parameters are obtained from recorded sympathetic skin response data by using Matlab software. The relationship between SSR parameters and laboratory tests is investigated by using artificial neural networks. As a result SSR seems to be a valid parameter in the classification of FMS.