OBJECTIVES: We report on the implementation of digital processing in a large clinical and research sleep laboratory. The system includes the digital collection, display, analysis, and repository of physiological signals collected during sleep. METHODS: After describing the original analog system, the computer equipment and software necessary for the digital implementation are presented and we explain our algorithms for rapid eye movement (REM) and delta-wave detection. Finally, we describe an experiment validating the digital system of display and analyses. CONCLUSIONS: The digital processing of sleep signals saves computer operator, polysomnographic technologist, and computer time. It also saves resources such as polysomnographic paper and FM tape. The digital signals lend themselves to a large array of analysis techniques and result in improved signal quality. Automated REM and delta-wave detection via digital processing correlate highly with visual counts of rapid eye movements and delta waves.
OBJECTIVES: We report on the implementation of digital processing in a large clinical and research sleep laboratory. The system includes the digital collection, display, analysis, and repository of physiological signals collected during sleep. METHODS: After describing the original analog system, the computer equipment and software necessary for the digital implementation are presented and we explain our algorithms for rapid eye movement (REM) and delta-wave detection. Finally, we describe an experiment validating the digital system of display and analyses. CONCLUSIONS: The digital processing of sleep signals saves computer operator, polysomnographic technologist, and computer time. It also saves resources such as polysomnographic paper and FM tape. The digital signals lend themselves to a large array of analysis techniques and result in improved signal quality. Automated REM and delta-wave detection via digital processing correlate highly with visual counts of rapid eye movements and delta waves.
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