Zang Junbin, An Qi, Li Bo, Zhang Zhidong, Gao Libo, Xue Chenyang
College of Information Engineering, Shanxi College of Technology, Shuozhou, 036000, China.
Key Laboratory of Instrumentation Science and Dynamic Measurement Ministry of Education, North University of China, 030051, Taiyuan, China.
Microsyst Nanoeng. 2025 Jan 15;11(1):7. doi: 10.1038/s41378-024-00858-3.
The alarming prevalence and mortality rates associated with cardiovascular diseases have emphasized the urgency for innovative detection solutions. Traditional methods, often costly, bulky, and prone to subjectivity, fall short of meeting the need for daily monitoring. Digital and portable wearable monitoring devices have emerged as a promising research frontier. This study introduces a wearable system that integrates electrocardiogram (ECG) and phonocardiogram (PCG) detection. By ingeniously pairing a contact-type PZT heart sound sensing structure with ECG electrodes, the system achieves the acquisition of high-quality ECG and PCG signals. Notably, the signal-to-noise ratios (SNR) for ECG and PCG signals were measured at 44.13 dB and 30.04 dB, respectively, demonstrating the system's remarkable stability across varying conditions. These collected signals were subsequently utilized to derive crucial feature values, including electromechanical delay (EMD), left ventricular ejection time (LVET), and pre-ejection period (PEP). Furthermore, we collected a dataset comprising 40 cases of ECG and PCG signals, enabling a comparative analysis of these three feature parameters between healthy individuals and coronary heart disease patients. This research endeavor presents a significant step forward in the realm of early, non-invasive, and intelligent monitoring of cardiovascular diseases, offering hope for earlier detection and more effective management of these life-threatening conditions.
心血管疾病令人担忧的患病率和死亡率凸显了创新检测解决方案的紧迫性。传统方法往往成本高昂、体积庞大且容易受到主观因素影响,无法满足日常监测的需求。数字和便携式可穿戴监测设备已成为一个有前景的研究前沿领域。本研究介绍了一种集成心电图(ECG)和心音图(PCG)检测的可穿戴系统。通过巧妙地将接触式PZT心音传感结构与ECG电极配对,该系统实现了高质量ECG和PCG信号的采集。值得注意的是,ECG和PCG信号的信噪比(SNR)分别测量为44.13dB和30.04dB,表明该系统在不同条件下具有出色的稳定性。随后,利用这些采集到的信号得出关键特征值,包括机电延迟(EMD)、左心室射血时间(LVET)和射血前期(PEP)。此外,我们收集了一个包含40例ECG和PCG信号的数据集,能够对健康个体和冠心病患者之间的这三个特征参数进行对比分析。这项研究工作在心血管疾病的早期、非侵入性和智能监测领域向前迈出了重要一步,为这些危及生命的疾病的早期检测和更有效的管理带来了希望。