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Wrist activity measured with a piezoceramic transducer was digitized and analyzed together with subjects' sleep/wake status to derive an optimal method for automatic computer sleep/wake scoring. Several algorithms for quantifying periods of activity were considered, and an algorithm that summed changes in activity level over a 2-s interval was found most sensitive. A computer program for scoring sleep/wake from the resulting digital activity records was then developed, and parameters derived by comparison with subjects' sleep/wake status as determined by EEG. EEG and activity sleep/wake scores agreed 94.46% of the time. A further prospective test of the automatic scoring system with new data yielded agreement of 96.02%. Finally, the data collection and recording functions were implemented in a wearable microprocessor-based digital activity monitor. The automatic scoring program was adjusted to use activity data collected by this monitor, and agreed 93.88% with EEG scoring. A prospective test with new data agreed 93.04% with EEG. Automatic scoring of activity data for sleep/wake is not only fast and accurate, but allows sleep to be monitored in non-laboratory situations. In addition, the score is objective and reliable, and free of scorer bias and drift.
Webster et al. (Wed,) studied this question.