TY  - JOUR
A1  - Röthenbacher, Annika
A1  - Cesari, Matteo
A1  - Doppler, Christopher E.J.
A1  - Okkels, Niels
A1  - Willemsen, Nele
A1  - Sembowski, Nora
A1  - Seger, Aline
A1  - Lindner, Marie
A1  - Brune, Corinna
A1  - Stefani, Ambra
A1  - Högl, Birgit
A1  - Bialonski, Stephan
A1  - Borghammer, Per
A1  - Fink, Gereon R.
A1  - Schober, Martin
A1  - Sommerauer, Michael
T1  - RBDtector: an open-source software to detect REM sleep without atonia according to visual scoring criteria
JF  - Scientific Reports
N2  - REM sleep without atonia (RSWA) is a key feature for the diagnosis of rapid eye movement (REM) sleep behaviour disorder (RBD). We introduce RBDtector, a novel open-source software to score RSWA according to established SINBAR visual scoring criteria. We assessed muscle activity of the mentalis, flexor digitorum superficialis (FDS), and anterior tibialis (AT) muscles. RSWA was scored manually as tonic, phasic, and any activity by human scorers as well as using RBDtector in 20 subjects. Subsequently, 174 subjects (72 without RBD and 102 with RBD) were analysed with RBDtector to show the algorithm’s applicability. We additionally compared RBDtector estimates to a previously published dataset. RBDtector showed robust conformity with human scorings. The highest congruency was achieved for phasic and any activity of the FDS. Combining mentalis any and FDS any, RBDtector identified RBD subjects with 100% specificity and 96% sensitivity applying a cut-off of 20.6%. Comparable performance was obtained without manual artefact removal. RBD subjects also showed muscle bouts of higher amplitude and longer duration. RBDtector provides estimates of tonic, phasic, and any activity comparable to human scorings. RBDtector, which is freely available, can help identify RBD subjects and provides reliable RSWA metrics.
Y1  - 2022
U6  - http://dx.doi.org/10.1038/s41598-022-25163-9
SN  - 2045-2322
VL  - 12
IS  - Article number: 20886
SP  - 1
EP  - 14
PB  - Springer Nature
CY  - London
ER  -