Early diagnosis of REM sleep disorders using a minimalistic polysomnography device (MiniPSG) and advanced machine learning methods for analysis of the sleep recordings.

Parkinson's disease (PD) is a progressive neurological condition that often begins with nonmotor symptoms appearing up to 20 years before a clinical diagnosis. In about one-third of patients, isolated REM sleep behavior disorder (iRBD) emerges before motor symptoms. This project uses an innovative method, MiniPSG, to automatically stage sleep and measure REM sleep without atonia (RSWA). Designed with a minimal number of electrodes, this approach is suitable for repeated recordings in patients' homes. By identifying the earliest signs of iRBD and exploring its relationship with clinical and imaging measures, this project aims to advance early detection and prognosis of prodromal PD.

• Professor Per Borghammer
• Klinisk Institut