Actigraphy-Based Assessment of Sleep Parameters

Details

• Personal Author:
  Andrew, Michael E. ; Fekedulegn D ; Innes KE ; Knox S ; Shi M ; Violanti JM
• Description:
  Actigraphy, a method for inferring sleep/wake patterns based on movement data gathered using actigraphs, is increasingly used in population-based epidemiologic studies because of its ability to monitor activity in natural settings. Using special software, actigraphic data are analyzed to estimate a range of sleep parameters. To date, despite extensive application of actigraphs in sleep research, published literature specifically detailing the methodology for derivation of sleep parameters is lacking; such information is critical for the appropriate analysis and interpretation of actigraphy data. Reporting of sleep parameters has also been inconsistent across studies, likely reflecting the lack of consensus regarding the definition of sleep onset and offset. In addition, actigraphy data are generally underutilized, with only a fraction of the sleep parameters generated through actigraphy routinely used in current sleep research. The objectives of this paper are to review existing algorithms used to estimate sleep/wake cycles from movement data, demonstrate the rules/methods used for estimating sleep parameters, provide clear technical definitions of the parameters, and suggest potential new measures that reflect intraindividual variability. Utilizing original data collected using Motionlogger Sleep Watch (Ambulatory Monitoring Inc., Ardsley, NY), we detail the methodology and derivation of 29 nocturnal sleep parameters, including those both widely and rarely utilized in research. By improving understanding of the actigraphy process, the information provided in this paper may help: ensure appropriate use and interpretation of sleep parameters in future studies; enable the recalibration of sleep parameters to address specific goals; inform the development of new measures; and increase the breadth of sleep parameters used. [Description provided by NIOSH]
• Subjects:
  Epidemiology Law Enforcement Occupational Health Safety Sleep Software
• Keywords:
  Author Keywords: Actigraphy BCOPS Computer Software Monitoring Systems Motionlogger Sleep Watch Police Officers Sleep/Wake Algorithms Sleep Parameters Wearable Technologies
• ISSN:
  2398-7308
• Document Type:
  Text
• Funding:
  Contract
• Genre:
  Journal Article
• Place as Subject:
  New York ; OSHA Region 2 ; OSHA Region 3 ; West Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  HELD - Health Effects Laboratory Division
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  350-367
• Volume:
  64
• Issue:
  4
• NIOSHTIC Number:
  nn:20058660
• Citation:
  Ann Work Expo Health 2020 May; 64(4):350-367
• Contact Point Address:
  Desta Fekedulegn, Bioanalytics Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, 1095 Willowdale Rd., Morgantown, WV 26505
• Email:
  djf7@cdc.gov
• Federal Fiscal Year:
  2020
• NORA Priority Area:
  Public Safety
• Performing Organization:
  State University of New York at Buffalo
• Peer Reviewed:
  True
• Source Full Name:
  Annals of Work Exposures and Health
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:ae484f07823b8e9a8ba50a9a4a99f73a6817aae3d83c3c5d4fadc4e79748f0ebd1235b0f3b7464ab38bbd071aca193442493c2f3b141213257b7efbf8e92abbb
• Download URL:
  https://stacks.cdc.gov/view/cdc/221700/cdc_221700_DS1.pdf
• File Type:
  [PDF - 1.30 MB ]