Validation of an Integrated Software for the Detection of Rapid Eye Movement Sleep Behavior Disorder

Study Objectives and Design: Rapid eye movement sleep without atonia (RWA) is the polysomnographic hallmark of REM sleep behavior disorder (RBD). To partially overcome the disadvantages of manual RWA scoring, which is time consuming but essential for the accurate diagnosis of RBD, we aimed to validate software specifically developed and integrated with polysomnography for RWA detection against the gold standard of manual RWA quantification. Setting: Academic referral center sleep laboratory. Participants: Polysomnographic recordings of 20 patients with RBD and 60 healthy volunteers were analyzed. Interventions: N/A. Measurements and Results: Motor activity during REM sleep was quantified manually and computer assisted (with and without artifact detection) according to Sleep Innsbruck Barcelona (SINBAR) criteria for the mentalis ("any,"phasic, tonic electromyographic [EMG] activity) and the flexor digitorum superficialis (FDS) muscle (phasic EMG activity). Computer-derived indices (with and without artifact correction) for "any,"phasic, tonic mentalis EMG activity, phasic FDS EMG activity, and the SINBAR index ("any" mentalis + phasic FDS) correlated well with the manually derived indices (all Spearman rhos 0.66-0.98). In contrast with computerized scoring alone, computerized scoring plus manual artifact correction (median duration 5.4 min) led to a significant reduction of false positives for "any" mentalis (40%), phasic mentalis (40.6%), and the SINBAR index (41.2%). Quantification of tonic mentalis and phasic FDS EMG activity was not influenced by artifact correction. Conclusion: The computer algorithm used here appears to be a promising tool for REM sleep behavior disorder detection in both research and clinical routine. A short check for plausibility of automatic detection should be a basic prerequisite for this and all other available computer algorithms.