Measuring Sleep by Wrist Actigraph.

Abstract

Results from the first year of our contract (1978-79) indicated that sleep can be identified from recordings of wrist activity, eliminating the need for costly EEG or unreliable observational sleep recognition procedures. In the current contract year we have explored alternative activity transducers, transducer placements, and orientations. Results indicate that a crystal transducer is superior to alternative activity transducers, and it responds adequately in any orientation. We have also demonstrated that wrist activity measures are superior to head or ankle measures. We have investigated methods of artifact rejection and digital preprocessing in converting analog activity data to a digital activity score. A simple digital filtering technique was effective in cancelling 60 Hz electrical noise, a persistent artifact in our analog data. A method of enhancing as well as compressing activity data by summing changes in activity over a 2-second data epoch yields the best discrimination between sleep and wake. A computer program to recognize sleep from the digital activity score is being refined. Once an optimal algorithm for retrospective sleep recognition has been derived, its success in prospectively recognizing sleep from wrist activity will be evaluated. A portable model of a wearable prototype digital actigraphic recorder has also been manufactured. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1980
Accession Number
ADA102996

Entities

People

  • Daniel F. Kripke
  • Daniel J. Mullaney
  • John B. Webster
  • Sam Messin
  • William Mason

Organizations

  • University of California, San Diego

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programs
  • Computers
  • Converters
  • Data Compression
  • Databases
  • Frequency
  • Health Services
  • Medical Personnel
  • Orientation (Direction)
  • Preprocessing
  • Recognition
  • Recording Systems
  • Sleep Disorders
  • Tilt/Vibration Switches
  • Transducers
  • Wearable Technology

Readers

  • Circadian Sleep-Wake Regulation and Chronobiology
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Image Processing and Computer Vision.