Flexible Optical Fiber Sensor for Non-Invasive Continuous Monitoring of Human Physiological Signals.

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL Small Methods Pub Date : 2025-02-02 DOI:10.1002/smtd.202401368
Qi Yu, Ya-Nan Zhang, Lingxiao Jiang, Linqian Li, Xuegang Li, Jian Zhao
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引用次数: 0

Abstract

With increasing health awareness, monitoring human physiological signals for health status and disease prevention has become crucial. Non-invasive flexible wearable devices address issues like invasiveness, inconvenience, size, and continuous monitoring challenges in traditional devices. Among flexible sensors, optical fiber sensors (OFSs) stand out due to their excellent biocompatibility, anti-electromagnetic interference capabilities, and ability to monitor multiple signals simultaneously. This paper reviews the application of flexible optical fiber sensing technology (OFST) in monitoring human lung function, cardiovascular function, body parameters, motor function, and various physiological signals. It emphasizes the importance of continuous monitoring in personal health management, clinical settings, sports training, and emergency response. The review discusses challenges in OFST for continuous health signal monitoring and envisions its significant potential for future development. This technology underscores the importance of constant health signal monitoring and highlights the advantages and prospects of optical fiber sensing. Innovations in OFS for non-invasive continuous monitoring of physiological signals hold profound implications for materials science, sensing technology, and biomedicine.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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