EMG variance during polysomnography as an assessment for REM sleep behavior disorder

Sleep. 2007 Dec;30(12):1771-8. doi: 10.1093/sleep/30.12.1771.

Abstract

Study objectives: In a previous study, we validated a polysomnographic assessment for REM sleep behavior disorder (RBD). The method proved to be reliable but required slow, labor-intensive visual scoring of surface electromyogram (EMG) activity. We therefore developed a computerized metric to assess EMG variance and compared the results to those previously published for visual scoring, bed partner-rated RBD symptom scores, and clinical assessments by sleep medicine specialists.

Design: Retrospective validation of new computer algorithm.

Setting: Sleep research laboratory

Participants: Twenty-three subjects: 17 with neurodegenerative disorders (9 with probable or possible RBD), and 6 controls.

Interventions: N/A METHODS: We visually scored 2 consecutive nocturnal polysomnograms for each subject. A computer algorithm calculated the variance of the chin EMG during all 3-second mini-epochs, and compared variances during REM sleep to a threshold defined by variances during quiet NREM sleep. The percentage of all REM mini-epochs with variance above this threshold created a metric, which we refer to as the supra-threshold REM EMG activity metric (STREAM) for each subject.

Results: The STREAM correlated highly with the visually-derived score for RBD severity (Spearman rho = 0.87, P < 0.0001). A clinical impression of probable or possible RBD was associated to a similar extent with both STREAM (Wilcoxon rank sum test, P = 0.009) and the visually-derived score (P = 0.018). An optimal STREAM cutoff identified probable or possible RBD with 100% sensitivity and 71% specificity. The RBD symptom score correlated with both STREAM (rho = 0.42, P = 0.046) and the visual score (rho = 0.42, P = 0.048).

Conclusions: These results suggest that a new, automated assessment for RBD may provide as much utility as a more time-consuming manual approach.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Algorithms
  • Data Display
  • Electromyography / instrumentation*
  • Female
  • Humans
  • Male
  • Mathematical Computing
  • Middle Aged
  • Neurodegenerative Diseases / complications
  • Neurodegenerative Diseases / diagnosis
  • Polysomnography / instrumentation*
  • REM Sleep Behavior Disorder / diagnosis*
  • REM Sleep Behavior Disorder / etiology
  • ROC Curve
  • Signal Processing, Computer-Assisted / instrumentation*