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Sleep-Stage Decision Algorithm by Using Heartbeat and Body-Movement Signals

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PROJECT TITLE :

Sleep-Stage Decision Algorithm by Using Heartbeat and Body-Movement Signals

ABSTRACT:

This paper describes a noninvasive algorithm to estimate the sleep stages used in the Rechtschaffen and Kales technique (R-K technique). The heartbeat and body-movement signals measured by the noninvasive pneumatic technique are used to estimate the sleep stages rather than using the Eletroencephalogram and Electromyography within the R-K method. From the noninvasive measurements, we have a tendency to defined 2 indices that indicate the condition of REM sleep and therefore the sleep depth. Functions to obtain the incidence ratio and the standard deviation of the extracted elements for every sleep stage were conjointly determined, for every age group of the themes. Using these indices and functions, an algorithm to classify the themes' sleep stages was proposed. The mean agreement ratios between the sleep stages' data obtained from the proposed method and those from the de facto customary R-K methodology, for the stages categorized into six, five, and three, were fifty one.vip.c, fifty six.2p.c, and 77.5percent, and their corresponding mean values of kappa statistics were 0.twenty nine, zero.thirty-nine, and zero.forty eight, respectively. The proposed technique shows closer agreement with the result of R-K method than the similar noninvasive methodology presented earlier.


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Sleep-Stage Decision Algorithm by Using Heartbeat and Body-Movement Signals - 4.8 out of 5 based on 90 votes

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