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

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...

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Publicado en:Sleep Vol. 30; no. 12; pp. 1771 - 1779
Autores principales: Burns JW, Consens FB, Little RJ, Angell KJ, Gilman S, Chervin RD
Formato: Journal Article
Publicado: Oxford University Press / USA 2007 Dec 1
Acceso en línea:Ver este registro en EBSCOhost
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        atl: EMG variance during polysomnography as an assessment for REM sleep behavior disorder.
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          Burns JW
          Consens FB
          Little RJ
          Angell KJ
          Gilman S
          Chervin RD
        affil: Michigan Tech Research Institute, 3600 Green Court, Suite 100, Ann Arbor, MI 48105; joseph.burns@mtu.edu
      sug:
        subj:
          Electromyography Equipment and Supplies
          Parasomnias Diagnosis
          Polysomnography Equipment and Supplies
          Signal Processing, Computer Assisted Equipment and Supplies
          Aged
          Algorithms
          Data Display
          Female
          Male
          Mathematics
          Middle Age
          Neurodegenerative Diseases Complications
          Neurodegenerative Diseases Diagnosis
          Parasomnias Etiology
          ROC Curve
          Aged: 65+ years
          Middle Aged: 45-64 years
          Female
          Male
      ab: 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.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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