A Fuzzy System to Analyze SIVD Diseases Using the Transcranial Magnetic Stimulation

– The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia (SIVD) and to measure the effect of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis. I. INTRODUCTION Transcranial magnetic stimulation (TMS) is a non invasive diagnostic and therapeutic method without painful effects[1]. The low intensity electrical current produced by such stimulation is not absorbed by the encephalic structures as it arises during the electrical stimulation. After getting over the encephalon, the current reaches without distortion the muscles and the skin receptors and is well tolerated by the subject under test. Since the muscle movements depend on the subject's health conditions, the use of TMS is in principle suitable to discover not only the case in which a subject is affected by some mental diseases [2] (e.g., dementia, Alzhaimer's disease, etc.) but also to what extent the subject is affected by such problems and what type of parameters the mental disease has modified with respect to the normal value in order to define some appropriate therapy. A suitable signal processing of the muscular responses is therefore necessary.