RBDtector

RBDtector detects REM sleep without atonia (RSWA) by applying the SINBAR visual scoring criteria to assess muscle activity.

Key Features:

• Muscle Activity Assessment: Evaluates muscle activity in the mentalis, flexor digitorum superficialis (FDS), and anterior tibialis (AT).
• Scoring System: Scores muscle activity as tonic, phasic, or any activity in accordance with SINBAR visual scoring criteria.
• Algorithmic Performance: In a study of 20 subjects, demonstrated robust conformity with manual scoring and highest congruency for phasic and any activity of the FDS.
• Diagnostic Accuracy: In a cohort of 174 subjects (72 without RBD and 102 with RBD) identified RBD subjects with 100% specificity and 96% sensitivity using a 20.6% cut-off, with performance maintained without manual artifact removal.
• Muscle Bout Characteristics: Identifies muscle bouts in RBD subjects that exhibit higher amplitude and longer duration.

Scientific Applications:

• RBD diagnosis: Automated detection of RSWA to support diagnosis of rapid eye movement sleep behavior disorder (RBD).
• Cohort and large-scale studies: Quantification of RSWA metrics for group studies and research cohorts without extensive manual scoring.

Methodology:

Applies the SINBAR visual scoring criteria to assess activity in the mentalis, FDS, and AT, categorizes activity as tonic, phasic, or any, and classifies subjects using a 20.6% RSWA cut-off with performance reported both with and without manual artifact removal.