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Method for detection of an abnormal sleep pattern in a person

This paper was not found in any repository; the policy of its publisher is unknown or unclear.
This paper was not found in any repository; the policy of its publisher is unknown or unclear.

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Abstract

The present disclosure relates to a method for detection of an abnormal sleep pattern based on a dataset of Electrooculography (EOG) signals obtained from a sleeping subject over a time interval, the method comprising the steps of dividing the time interval into a plurality of subintervals, each subinterval preferably corresponding to a sleep epoch, classifying each subinterval in terms of sleep stages, thereby obtaining a temporal sleep stage pattern, wherein a subject having an uncharacteristic temporal distribution of sleep stages is characterized as having an abnormal sleep pattern.