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REM sleep estimation only using respiratory dynamics

Gih Sung Chung1, Byung Hoon Choi1, Jin-Seong Lee2, Jeong Su Lee1, Do-Un Jeong3 and Kwang Suk Park4,5

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Polysomnography (PSG) is currently considered the gold standard for assessing sleep quality. However, the numerous sensors that must be attached to the subject can disturb sleep and limit monitoring to within hospitals and sleep clinics. If data could be obtained without such constraints, sleep monitoring would be more convenient and could be extended to ordinary homes. During rapid-eye-movement (REM) sleep, respiration rate and variability are known to be greater than in other sleep stages. Hence, we calculated the average rate and variability of respiration in an epoch (30 s) by applying appropriate smoothing algorithms. Increased and irregular respiratory patterns during REM sleep were extracted using adaptive and linear thresholds. When both parameters simultaneously showed higher values than the thresholds, the epochs were assumed to belong to REM sleep. Thermocouples and piezoelectric-type belts were used to acquire respiratory signals. Thirteen healthy adults and nine obstructive sleep apnea (OSA) patients participated in this study. Kappa statistics showed a substantial agreement (κ > 0.60) between the standard and respiration-based methods. One-way ANOVA analysis showed no significant difference between the techniques for total REM sleep. This approach can also be applied to the non-intrusive measurement of respiration signals, making it possible to automatically detect REM sleep without disturbing the subject.


PACS

87.80.-y Biophysical techniques (research methods)

87.19.L- Neuroscience

87.19.U- Hemodynamics

Subjects

Instrumentation and measurement

Medical physics

Biological physics

Dates

Issue 12 (December 2009)

Received 1 March 2009, accepted for publication 2 October 2009

Published 28 October 2009



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