Sliding Trend Fuzzy Approximate Entropy as a Novel Descriptor of Heart Rate Variability in Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a common sleep disorder that is often associated with reduced heart rate variability (HRV), thus reflecting modulation of the autonomic system. Sliding trend fuzzy approximate entropy (SlTr-fApEn), which is based on the empirical mode decomposition (EMD) method, has...

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Veröffentlicht in:IEEE journal of biomedical and health informatics 2019-01, Vol.23 (1), p.175-183
Hauptverfasser: Li, Yifan, Pan, Weifeng, Li, Kunyang, Jiang, Qing, Liu, Guanzheng
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Sprache:eng
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Zusammenfassung:Obstructive sleep apnea (OSA) is a common sleep disorder that is often associated with reduced heart rate variability (HRV), thus reflecting modulation of the autonomic system. Sliding trend fuzzy approximate entropy (SlTr-fApEn), which is based on the empirical mode decomposition (EMD) method, has been proposed as a novel index for analyzing HRV with OSA. This study included 60 electrocardiogram recordings from the PhysioNet database (40 OSA recordings and 20 healthy recordings) with apnea or no apnea in 5-minute segments. HRV indices obtained by sliding trend analysis were compared to those obtained by time-frequency domain analysis. Among all indices, the ratio of low-frequency power and high-frequency power (LF/HF) and sliding trend indices could significantly differentiate OSA recordings from normal recordings (p
ISSN:2168-2194
2168-2208
DOI:10.1109/JBHI.2018.2790968