RBDtector: an open-source software to detect REM sleep without atonia according to visual scoring criteria
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, fle...
Saved in:
Published in | Scientific reports Vol. 12; no. 1; pp. 20886 - 14 |
---|---|
Main Authors | , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
03.12.2022
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | 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. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-022-25163-9 |