External validation of a data-driven algorithm for muscular activity identification during sleep.

External validation of a data-driven algorithm for muscular activity identification during sleep. J Sleep Res. 2019 May 26;:e12868 Authors: Cesari M, Christensen JAE, Sorensen HBD, Jennum P, Mollenhauer B, Muntean ML, Trenkwalder C, Sixel-Döring F Abstract Several automated methods for scoring periodic limb movements during sleep (PLMS) and rapid eye movement (REM) sleep without atonia (RSWA) have been proposed, but most of them were developed and validated on data recorded in the same clinic, thus they may be biased. This work aims to validate our data-driven algorithm for muscular activity detection during sleep, originally developed based on data recorded and manually scored at the Danish Center for Sleep Medicine. The validation was carried out on a cohort of 240 participants, including de novo Parkinson's disease (PD) patients and neurologically healthy controls, whose sleep data were recorded and manually evaluated at Paracelsus-Elena Klinik, Kassel, Germany. In the German cohort, the algorithm showed generally good agreement between manual and automated PLMS indices, and identified with 88.75% accuracy participants with PLMS index above 15 PLMS per hour of sleep, and with 84.17% accuracy patients suffering from REM sleep behaviour disorder (RBD) showing RSWA. By comparing the algorithm performances in the Danish and German cohorts, we hypothesized that inter-clinical differences may exist in the way limb movements are manuall...
Source: Journal of Sleep Research - Category: Sleep Medicine Authors: Tags: J Sleep Res Source Type: research