Department of Biomedical Engineering, College of Health Science, Yonsei University, Wonju, Kangwon-do, 26493, Republic of Korea.
Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
J Med Syst. 2017 Sep 26;41(11):177. doi: 10.1007/s10916-017-0824-2.
This study investigates the feasibility of cardiopulmonary coupling (CPC) using home sleep monitoring system. We have designed a system to measure respiratory signals and normal-to-normal (NN) interval series in a non-contact based on air mattress. Then, CPC analysis was conducted using extracted respiratory signals and NN interval series, and six CPC parameters were extracted (VLFC, LFC, HFC, e-LFC, e-LFC and e-LFC). To evaluate the proposed method, two statistical analyses were conducted between the CPC parameters extracted by the electrocardiogram-based conventional method and the air mattress-based proposed method for five patients with obstructive sleep apnea and hypopnea (OSAH). Wilcoxon's signed rank test on the CPC parameters of the two methods indicated no significant differences (p > 0.05) and Spearman's rank correlation analysis showed high positive correlations (r ≥ 0.7, p < 0.05) between the two methods. Therefore, the proposed method has the potential for performing CPC analysis using air mattress-based system.
本研究旨在探讨使用家庭睡眠监测系统进行心肺耦合（CPC）的可行性。我们设计了一种基于空气床垫的非接触式系统来测量呼吸信号和正常到正常（NN）间隔序列。然后，使用提取的呼吸信号和 NN 间隔序列进行 CPC 分析，并提取了六个 CPC 参数（VLFC、LFC、HFC、e-LFC、e-LFC 和 e-LFC）。为了评估所提出的方法，对 5 例阻塞性睡眠呼吸暂停低通气（OSAH）患者的心电图传统方法和空气床垫基于方法提取的 CPC 参数进行了两项统计学分析。两种方法的 CPC 参数的 Wilcoxon 符号秩检验无显著差异（p>0.05），Spearman 等级相关分析显示两种方法具有高度正相关（r≥0.7，p<0.05）。因此，该方法具有使用基于空气床垫的系统进行 CPC 分析的潜力。
