Observations on muscle activity in REM sleep behavior disorder assessed with a semi-automated scoring algorithm.

OBJECTIVES

Rapid eye movement (REM) sleep behavior disorder (RBD) is defined by dream enactment due to a failure of normal muscle atonia. Visual assessment of this muscle activity is time consuming and rater-dependent.

METHODS

An EMG computer algorithm for scoring 'tonic', 'phasic' and 'any' submental muscle activity during REM sleep was evaluated compared with human visual ratings. Subsequently, 52 subjects were analyzed with the algorithm. Duration and maximal amplitude of muscle activity, and self-awareness of RBD symptoms were assessed.

RESULTS

The computer algorithm showed high congruency with human ratings and all subjects with RBD were correctly identified by excess of submental muscle activity, when artifacts were removed before analysis. Subjects with RBD exhibited prolonged bouts of 'phasic' muscle activity with high amplitude. Self-awareness of RBD symptoms correlated with amount of REM sleep without atonia.

CONCLUSIONS

Our proposed algorithm was able to detect and rate REM sleep without atonia allowing identification of RBD. Increased duration and amplitude of muscle activity bouts were characteristics of RBD. Quantification of REM sleep without atonia represents a marker of RBD severity.

SIGNIFICANCE

Our EMG computer algorithm can support a diagnosis of RBD while the quantification of altered muscle activity provides a measure of its severity.