• DocumentCode
    2966832
  • Title

    Feasibility of a simple method for identifying sleep periods from Holter recordings

  • Author

    Williams, C. ; Stein, PK ; Domitrovich, PP ; Taylor, TR

  • Author_Institution
    Washington Univ. Sch. of Med., St. Louis, MO, USA
  • fYear
    2002
  • fDate
    22-25 Sept. 2002
  • Firstpage
    533
  • Lastpage
    536
  • Abstract
    To determine whether sleep periods can be identified from Holter-derived data using a combination of hourly average HR patterns and hourly spectral plots, Holier data from N=77 randomly-selected subjects with self-reported bed:wake (B:W) times were examined. N=50 were patients with a recent MI (C), 12 were younger subjects from a Holler quality validation study (Y), and 15 were subjects>65 years old from the Cardiovascular Health Study (O). N=18 (C) were excluded for a combination of abnormal circadian rhythm and abnormal HRV plots. The accuracy of hourly HR+HRV patterns to identify bedtime ±1 hr was: 100% (O), 84% (C), and 100% (Y). Hourly HR+HRV patterns identified wake-times ±1 hr 100% of the time for (O), 91% for (C) and 100% (Y). Identification of sleep periods from Holter data appears feasible in different groups using a simple algorithm. This method could permit detailed study of sleep periods in Holter cohorts where diaries are unavailable.
  • Keywords
    electrocardiography; medical signal processing; sleep; Cardiovascular Health Study; Holter recordings; MI; abnormal HRV plots; abnormal circadian rhythm; hourly average patterns; hourly spectral plots; quality validation study; randomly-selected subjects; self reported bed/wake times; sleep period identification; Cardiology; Circadian rhythm; Frequency estimation; Heart rate; Heart rate measurement; Heart rate variability; Hospitals; Muscles; Sleep; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers in Cardiology, 2002
  • ISSN
    0276-6547
  • Print_ISBN
    0-7803-7735-4
  • Type

    conf

  • DOI
    10.1109/CIC.2002.1166827
  • Filename
    1166827