Gabriele Salvatore Giarrusso
Machine Learning Strategies for Single-Channel EEG Automatic Detection of REM Sleep Behavior Disorder: a Model Based on REM and Slow Wave Sleep.
Rel. Gabriella Olmo, Irene Rechichi. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2023
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Abstract
Human Sleep is the cyclic repetition of states characterized by different processes which play an important role in a wide range of activities, such as restoring the body's energy as well as supporting memory consolidation, and clearance of metabolic waste products generated by awake brain neural activity. It is mainly divided into two macro-stages, namely Rapid-Eye movement (REM) sleep and non-Rapid-Eye movement (NREM) sleep which, accordingly to the American Academy of Sleep Medicine (AASM) guidelines, is further characterized by three stages N1, N2, and N3 (or Slow Wave Sleep). In recent years, Sleep Disorders got the researchers' attention and some studies demonstrated a strong correlation with some types of Neurodegenerative Disease pathogenesis.
Remarkably, Idiopathic REM Sleep Behavior Disorder (iRBD) shows the strongest correlation with the family of alpha-synucleinopathies, e.g
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