Methods for obtaining and analyzing unattended polysomnography data for a multicenter study

Susan Redline, Mark H. Sanders, Bonnie K. Lind, Stuart F. Quan, Conrad Iber, Daniel J. Gottlieb, William H. Bonekat, David M. Rapoport, Philip L. Smith, James P. Kiley

Research output: Contribution to journalArticlepeer-review

433 Scopus citations


This paper reviews the data collection, processing, and analysis approaches developed to obtain comprehensive unattended polysomnographic data for the Sleep Heart Health Study, a multicenter study of the cardiovascular consequences of sleep-disordered breathing. Protocols were developed and implemented to standardize in-home data collection procedures and to perform centralized sleep scoring. Of 7027 studies performed on 6697 participants, 5 534 studies were determined to be technically acceptable (failure rate 5.3%). Quality grades varied over time, reflecting the influences of variable technician experience, and equipment aging and modifications. Eighty-seven percent of studies were judged to be of 'good' quality or better, and 75% were judged to be of sufficient quality to provide reliable sleep staging and arousal data. Poor submental EMG (electromyogram) accounted for the largest proportion of poor signal grades (9% of studies had <2 hours artifact free EMG signal). These data suggest that with rigorous training and clear protocols for data collection and processing, good-quality multichannel polysomnography data can be obtained for a majority of unattended studies performed in a research setting. Data most susceptible to poor signal quality are sleep staging and arousal data that require clear EEG (electroencephalograph) and EMG signals.

Original languageEnglish (US)
Pages (from-to)759-767
Number of pages9
Issue number7
StatePublished - Nov 1 1998
Externally publishedYes


  • Epidemiology
  • Polysomnography
  • Sleep apnea

ASJC Scopus subject areas

  • Clinical Neurology
  • Physiology (medical)


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