Analysis of U-Shape Patterns in RR-Interval Time Series During Sleep

The proposed study investigates a phenomenon, defined as "U-patterns", that takes place in the RR-interval time series during sleep. These patterns are defined as a U-shaped decrease-increase in the RR-intervals, with a duration of 20 to 40 seconds with a minimum decrease of 15% in the local RR-interval mean value. This paper studies statistical characteristics of U-patterns on subjects undergoing sleep deprivation. 15 healthy subjects (7males, 22.1 +/- 1.7 yrs.) participated in an experiment over a span of 17 days, in three successive stages. A baseline phase of seven days, during which the subjects slept normally; A sleep deprivation phase of three days, during which they could only sleep three hours per night; Finally, in a 7-day recovery phase subjects went back to sleeping normally, as they would in the baseline phase. While sleeping, polysomnographic data was recorded from the participants. U-patterns were extracted and their statistical characteristics were analyzed. Alongside the incidence of these patterns, their depth, duration and area were measured. U-patterns were present in all participating subjects. Moreover, these patterns were recurrent in all RR-interval time series. There was a significant difference in their repetition rate, depth and duration from baseline to sleep-deprivation and recovery. Results show that the characteristics of U-patterns change when subjects are undergoing sleep deprivation, suggesting these patterns can be used to identify patients suffering from sleep disorders.

Published in:
2018 Computing In Cardiology Conference (Cinc)
Presented at:
45th Computing in Cardiology Conference (CinC), Maastricht, NETHERLANDS, Sep 23-26, 2018
Jan 01 2018
New York, IEEE

 Record created 2019-09-15, last modified 2019-12-05

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