Abstract
The paper proposes a methodology based on a neural network to process the signals related to the hands movements in response to the Transcranial Magnetic Stimulation (TMS) in order to diagnose the pathology and evaluate the treatment of the patients affected by demency diseases. First a time-frequency analysis of such signals is carried out to identify the main signal variables that characterize the demency diseases. Then these variables are processed by a neural network in order to classify the responses into four classes: healthy subjects, people affected by Subcortical Ischemic Vascular Dementia (SIVD) and/or Alzheimer. A comparison between the proposed method and a fuzzy approach previously developed by the authors is presented.
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References
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Faro, A., Giordano, D., Pennisi, M., Scarciofalo, G., Spampinato, C., Tramontana, F. (2005). Transcranial Magnetic Stimulation (TMS) to Evaluate and Classify Mental Diseases Using Neural Networks. In: Miksch, S., Hunter, J., Keravnou, E.T. (eds) Artificial Intelligence in Medicine. AIME 2005. Lecture Notes in Computer Science(), vol 3581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527770_43
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DOI: https://doi.org/10.1007/11527770_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27831-3
Online ISBN: 978-3-540-31884-2
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