A Novel Magnetic Respiratory Sensor for Human Healthcare

被引:5
作者
Hwang, Kee Young [1 ]
Jimenez, Valery Ortiz [1 ]
Muchharla, Baleeswaraiah [1 ]
Eggers, Tatiana [1 ]
Le Anh-Tuan [2 ]
Lam Vu Dinh [3 ]
Phan, Manh-Huong [1 ]
机构
[1] Univ S Florida, Dept Phys, Tampa, FL 33620 USA
[2] Phenikaa Univ, Phenikaa Univ Nano Inst PHENA, Hanoi 12116, Vietnam
[3] Vietnam Acad Sci & Technol, Grad Univ Sci & Technol GUST, 18 Hoang Quoc Viet, Hanoi 12116, Vietnam
来源
APPLIED SCIENCES-BASEL | 2021年 / 11卷 / 08期
关键词
breathing; respiratory; magnetic sensor; rehabilitation therapies; healthcare; BREATH; SARS-COV-2; VIRUS;
D O I
10.3390/app11083585
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Featured Application A magnetic respiratory sensor can be potentially employed to identify respiratory-related diseases like COVID-19 and track its progress in real time. Breathing is vital to life. Therefore, the real-time monitoring of a patient ' s breathing pattern is crucial to respiratory rehabilitation therapies, such as magnetic resonance exams for respiratory-triggered imaging, chronic pulmonary disease treatment, and synchronized functional electrical stimulation. While numerous respiratory devices have been developed, they are often in direct contact with a patient, which can yield limited data. In this study, we developed a novel, non-invasive, and contactless magnetic sensing platform that can precisely monitor a patient ' s breathing, movement, or sleep patterns, thus providing efficient monitoring at a clinic or home. A magneto-LC resonance (MLCR) sensor converts the magnetic oscillations generated by a patient ' s breathing into an impedance spectrum, which allows for a deep analysis of one ' s breath variation to identify respiratory-related diseases like COVID-19. Owing to its ultrahigh sensitivity, the MLCR sensor yields a distinct breathing pattern for each patient tested. It also provides an accurate measure of the strength of a patient ' s breath at multiple stages as well as anomalous variations in respiratory rate and amplitude. The sensor can thus be applied to detect symptoms of COVID-19 in a patient, due to shortness of breath or difficulty breathing, as well as track the disease ' s progress in real time.
引用
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页数:10
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