C. Skjaerbaek, A. T. Damgaard, N. B. Bertelsen, T. P. Lillethorup, J. Horsager, V. Lowe, N. H. Andersen, A. J. Terkelsen, M. Otto, D. Bertram, M. Rodemann, S. L. Kappel, Y. R. Tabar, M. Sommerauer, P. Borghammer, P. Kidmose
Isolated REM sleep behaviour disorder (RBD) is the strongest prodromal marker of Parkinson's disease (PD) and dementia with Lewy bodies, yet diagnosis requires video-polysomnography with assisted montage and expert scoring and does not scale to screening or trial enrichment. We developed a fully automated, self-applied system that detects RBD from a pair of electrodes placed behind the ears, with no manual scoring at any stage. A novel bipolar mastoid ExG derivation enables both sleep staging and quantification of REM sleep without atonia (RWA). A fine-tuned deep-learning 1-channel model staged sleep at a Cohen's kappa of 0.65 in PD, iRBD and controls ({kappa} = 0.73 for the 2-channel model). Automated mastoid RWA correlated strongly with expert chin SINBAR scoring (r = 0.82). In self-applied home recordings from 76 participants, the 1-channel system detected RBD with an AUC of 0.95 (sensitivity 94%, specificity 86%), reproduced on in-lab polysomnographies (AUC 0.93, n = 378). In RBD, between-night RWA variability warrants repeated nights for prognostic monitoring. The system provides a scalable tool for RBD detection and a continuous RWA measure for longitudinal studies of neurodegeneration.