The aim of this thesis work is to develop a machine-learning algorithm able to recognize and predict the progression of amyotrophic lateral sclerosis (ALS), which is commonly known as Lou Gehrig's disease. There is evidence that rapid eye movement (REM) sleep behaviour disorder (RBD) may serve as a precursor or early indicator of ALS, owing to the shared motor system dysfunction between the two conditions. Genetic or environmental factors might also contribute to the development of both diseases. Hence, this thesis examines several studies about RBD and REM sleep without atonia (RSWA), as they have been associated with various neurodegenerative pathologies, primarily those in the alpha-synucleinopathies group, such as Parkinson's disease and Dementia with Lewy bodies.