Validation of automated detection of REM sleep without atonia using in-laboratory and in-home recordings

Study Objectives: To evaluate the concordance between visual scoring and automated detection of rapid eye movement sleep without atonia (RSWA) and the validity and reliability of in-home automated-RSWA detection in patients with rapid eye movement sleep behavior disorder (RBD) and a control group. Methods: Sleep Profiler signals were acquired during simultaneous in-laboratory polysomnography in 24 isolated patients with RBD. Chin and arm RSWA measures visually scored by an expert sleep technologist were compared to algorithms designed to automate RSWA detection. In a second cohort, the accuracy of automated-RSWA detection for discriminating between RBD and control group (n = 21 and 42, respectively) was assessed in multinight in-home recordings. Results: For the in-laboratory studies, agreement between visual and auto-scored RSWA from the chin and arm were excellent, with intraclass correlations of 0.89 and 0.95, respectively, and substantial, based on Kappa scores of 0.68 and 0.74, respectively. For classification of patients with iRBD vs controls, specificities derived from auto-detected RSWA densities obtained from in-home recordings were 0.88 for the chin, 0.93 for the arm, and 0.90 for the chin or arm, while the sensitivities were 0.81, 0.81, and 0.86, respectively. The night-to-night consistencies of the respective auto-detected RSWA densities were good based on intraclass correlations of 0.81, 0.79, and 0.84, however some night-to-night disagreements in abnormal RSWA detection were observed. Conclusions: When compared to expert visual RSWA scoring, automated RSWA detection demonstrates promise for detection of RBD. The night-to-night reliability of chin- and arm-RSWA densities acquired in-home were equivalent.