Rapid Eye Movement Behavior Disorder (RBD) refers to a condition in which patients act out their dreams and engage in potentially disruptive, injurious and even dangerous behavior while asleep[1-3]. Clinical reports of RBD have been shown to anticipate the development of neurodegenerative conditions like Parkinson's Disease by 20 years or more [4-6]. Despite this potential prognostic significance for human disease, the field of Sleep Medicine lacks an accepted computerized approach to quantify muscle activity in sleep. This proposed interdisciplinary research seeks to merge methods of computer engineering based computation with advanced neuroscience to establish a computerized clinical decision support system (CDSS) to detect RBD via measurement and analysis of the phasic electromyographic activity metric (PEM). The sponsor (Bliwise) has provided evidence based on traditional visual analyses from "expert" scorers that PEM recorded during sleep is a sensitive indicator a) to differentiate PD patients from controls ;b) to distinguish non-PD patients with a history of RBD from controls ;and c) to differentiate PD patients with early and late stage disease . These data suggest that computer-aided PEM detection within a user-friendly CDSS will be vital for clinicians to determine prognosis, track disease course, and, possibly, even monitor treatment.
The proposed work is envisioned as a vital and integral component to establish standardized computerized bio-signal processing methods to detect phasic muscle activity in overnight human sleep polysomnograms for the identification and treatment of Rapid Eye Movement Behavior Disorder.
|Fairley, Jacqueline A; Georgoulas, George; Smart, Otis L et al. (2014) Wavelet analysis for detection of phasic electromyographic activity in sleep: influence of mother wavelet and dimensionality reduction. Comput Biol Med 48:77-84|