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Health Monitoring via Heart, Breath, and Korotkoff Sounds by Wearable Piezoelectret Patches

心音图 心音 听诊器 医学 声音(地理) 血压 听诊 光容积图 可穿戴计算机 生物声学 生物医学工程 计算机科学 心脏病学 声学 内科学 无线 电信 放射科 嵌入式系统 物理
作者
Liuyang Han,Weijin Liang,Qisen Xie,Jingjing Zhao,Ying Dong,Xiaohao Wang,Lin Liu
出处
期刊:Advanced Science [Wiley]
卷期号:10 (28) 被引量:2
标识
DOI:10.1002/advs.202301180
摘要

Real-time monitoring of vital sounds from cardiovascular and respiratory systems via wearable devices together with modern data analysis schemes have the potential to reveal a variety of health conditions. Here, a flexible piezoelectret sensing system is developed to examine audio physiological signals in an unobtrusive manner, including heart, Korotkoff, and breath sounds. A customized electromagnetic shielding structure is designed for precision and high-fidelity measurements and several unique physiological sound patterns related to clinical applications are collected and analyzed. At the left chest location for the heart sounds, the S1 and S2 segments related to cardiac systole and diastole conditions, respectively, are successfully extracted and analyzed with good consistency from those of a commercial medical device. At the upper arm location, recorded Korotkoff sounds are used to characterize the systolic and diastolic blood pressure without a doctor or prior calibration. An Omron blood pressure monitor is used to validate these results. The breath sound detections from the lung/ trachea region are achieved a signal-to-noise ration comparable to those of a medical recorder, BIOPAC, with pattern classification capabilities for the diagnosis of viable respiratory diseases. Finally, a 6×6 sensor array is used to record heart sounds at different locations of the chest area simultaneously, including the Aortic, Pulmonic, Erb's point, Tricuspid, and Mitral regions in the form of mixed data resulting from the physiological activities of four heart valves. These signals are then separated by the independent component analysis algorithm and individual heart sound components from specific heart valves can reveal their instantaneous behaviors for the accurate diagnosis of heart diseases. The combination of these demonstrations illustrate a new class of wearable healthcare detection system for potentially advanced diagnostic schemes.
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