Liang Duan, Wu Shan, Tang Lan, Feng Kaicheng, Liu Guanzheng
School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou 510275, China.
Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Engineering, Sun Yat-Sen University, Guangzhou 510275, China.
Entropy (Basel). 2021 Feb 24;23(3):267. doi: 10.3390/e23030267.
Obstructive sleep apnea (OSA) is associated with reduced heart rate variability (HRV) and autonomic nervous system dysfunction. Sample entropy (SampEn) is commonly used for regularity analysis. However, it has limitations in processing short-term segments of HRV signals due to the extreme dependence of its functional parameters. We used the nonparametric sample entropy (NPSampEn) as a novel index for short-term HRV analysis in the case of OSA. The manuscript included 60 6-h electrocardiogram recordings (20 healthy, 14 mild-moderate OSA, and 26 severe OSA) from the PhysioNet database. The NPSampEn value was compared with the SampEn value and frequency domain indices. The empirical results showed that NPSampEn could better differentiate the three groups ( < 0.01) than the ratio of low frequency power to high frequency power (LF/HF) and SampEn. Moreover, NPSampEn (83.3%) approached a higher OSA screening accuracy than the LF/HF (73.3%) and SampEn (68.3%). Compared with SampEn (|r| = 0.602, < 0.05), NPSampEn (|r| = 0.756, < 0.05) had a significantly stronger association with the apnea-hypopnea index (AHI). Hence, NPSampEn can fully overcome the influence of individual differences that are prevalent in biomedical signal processing, and might be useful in processing short-term segments of HRV signal.
阻塞性睡眠呼吸暂停（OSA）与心率变异性（HRV）降低及自主神经系统功能障碍有关。样本熵（SampEn）常用于规律性分析。然而，由于其功能参数的极端依赖性，它在处理HRV信号的短期片段时存在局限性。我们将非参数样本熵（NPSampEn）作为OSA病例中短期HRV分析的新指标。该手稿纳入了PhysioNet数据库中的60份6小时心电图记录（20例健康者、14例轻中度OSA患者和26例重度OSA患者）。将NPSampEn值与SampEn值及频域指标进行比较。实证结果表明，与低频功率与高频功率之比（LF/HF）和SampEn相比，NPSampEn能更好地区分这三组（<0.01）。此外，NPSampEn（83.3%）的OSA筛查准确率高于LF/HF（73.3%）和SampEn（68.3%）。与SampEn（|r| = 0.602，<0.05）相比，NPSampEn（|r| = 0.756，<0.05）与呼吸暂停低通气指数（AHI）的相关性显著更强。因此，NPSampEn可以充分克服生物医学信号处理中普遍存在的个体差异的影响，可能有助于处理HRV信号的短期片段。
