Assessing REM Sleep Behaviour Disorder: From Machine Learning Classification to the Definition of a Continuous Dissociation Index.

Rapid Eye Movement Sleep Behaviour Disorder (RBD) is regarded as a prodrome of neurodegeneration, with a high conversion rate to α-synucleinopathies such as Parkinson's Disease (PD). The clinical diagnosis of RBD co-exists with evidence of REM Sleep Without Atonia (RSWA), a parasomnia that features loss of physiological muscular atonia during REM sleep. The objectives of this study are to implement an automatic detection of RSWA from polysomnographic traces, and to propose a continuous index (the Dissociation Index) to assess the level of dissociation between REM sleep stage and atonia.

Single-channel EEG classification of sleep stages based on REM microstructure.

Rapid-eye movement (REM) sleep, or paradoxical sleep, accounts for 20-25% of total night-time sleep in healthy adults and may be related, in pathological cases, to parasomnias. A large percentage of Parkinson's disease patients suffer from sleep disorders, including REM sleep behaviour disorder and hypokinesia; monitoring their sleep cycle and related activities would help to improve their quality of life. There is a need to accurately classify REM and the other stages of sleep in order to properly identify and monitor parasomnias.