Cardiovascular diseases are the main cause of death worldwide, with sleep disordered breathing being a further aggravating factor. Respiratory illnesses are the third leading cause of death amongst the noncommunicable diseases. The current COVID-19 pandemic, however, also highlights the impact of communicable respiratory syndromes. In the clinical routine, prolonged postanesthetic respiratory instability worsens the patient outcome. Even though early and continuous, long-term cardiorespiratory monitoring has been proposed or even proven to be beneficial in several situations, implementations thereof are sparse. We employed our recently presented, multimodal patch stethoscope to estimate Einthoven electrocardiogram (ECG) Lead I and II from a single 55 mm ECG lead. Using the stethoscope and ECG subsystems, the pre-ejection period (PEP) and left ventricular ejection time (LVET) were estimated. ECG-derived respiration techniques were used in conjunction with a novel, phonocardiogram-derived respiration approach to extract respiratory parameters. Medical-grade references were the SOMNOmedics SOMNO HDTM and Osypka ICON-CoreTM. In a study including 10 healthy subjects, we analyzed the performances in the supine, lateral, and prone position. Einthoven I and II estimations yielded correlations exceeding 0.97. LVET and PEP estimation errors were 10% and 21%, respectively. Respiratory rates were estimated with mean absolute errors below 1.2 bpm, and the respiratory signal yielded a correlation of 0.66. We conclude that the estimation of ECG, PEP, LVET, and respiratory parameters is feasible using a wearable, multimodal acquisition device and encourage further research in multimodal signal fusion for respiratory signal estimation.

中文翻译：

---

使用多模态数字贴片听诊器进行可穿戴心肺监测：使用 55 毫米单导联心电图和心音图估计心电图、PEP、LVET 和呼吸。


心血管疾病是全世界死亡的主要原因，睡眠呼吸障碍是进一步加重病情的因素。呼吸系统疾病是非传染性疾病中第三大死因。然而，当前的 COVID-19 大流行也凸显了传染性呼吸系统综合症的影响。在临床常规中，长时间的麻醉后呼吸不稳定会使患者的预后恶化。尽管早期、持续、长期的心肺监测已经被提出，甚至被证明在几种情况下是有益的，但其实施却很少。我们使用最近推出的多模式贴片听诊器来估计单个 55 毫米心电图导联的艾因托芬心电图 (ECG) 导联 I 和 II。使用听诊器和心电图子系统估计射血前期 (PEP) 和左心室射血时间 (LVET)。基于心电图的呼吸技术与一种新颖的基于心音图的呼吸方法结合使用来提取呼吸参数。医疗级参考是 SOMNOmedics SOMNO HDTM 和 Osypka ICON-CoreTM。在一项包括 10 名健康受试者的研究中，我们分析了仰卧位、侧卧位和俯卧位的表现。 Einthoven I 和 II 估计得出的相关性超过 0.97。 LVET 和 PEP 估计误差分别为 10% 和 21%。呼吸频率的估计平均绝对误差低于 1.2 bpm，呼吸信号产生的相关性为 0.66。我们的结论是，使用可穿戴多模态采集设备估计 ECG、PEP、LVET 和呼吸参数是可行的，并鼓励进一步研究用于呼吸信号估计的多模态信号融合。