Automatic detection of rapid eye movements (REMs): A machine learning approach.

Journal: Journal of neuroscience methods
Published Date: Feb 1, 2016

Abstract

BACKGROUND: Rapid eye movements (REMs) are a defining feature of REM sleep. The number of discrete REMs over time, or REM density, has been investigated as a marker of clinical psychopathology and memory consolidation. However, human detection of REMs is a time-consuming and subjective process. Therefore, reliable, automated REM detection software is a valuable research tool.

Authors

  • Benjamin D Yetton
    University of California, 900 University Ave, Riverside, CA 92521, United States.
  • Mohammad Niknazar
    University of California, 900 University Ave, Riverside, CA 92521, United States.
  • Katherine A Duggan
    University of California, 900 University Ave, Riverside, CA 92521, United States.
  • Elizabeth A McDevitt
    University of California, 900 University Ave, Riverside, CA 92521, United States.
  • Lauren N Whitehurst
    University of California, 900 University Ave, Riverside, CA 92521, United States.
  • Negin Sattari
    University of California, 900 University Ave, Riverside, CA 92521, United States.
  • Sara C Mednick
    University of California, 900 University Ave, Riverside, CA 92521, United States. Electronic address: smednick@ucr.edu.

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