Flexible Wearable Microfiber Respiratory Sensor Based on Microspheres Coupling

• Published in: IEEE sensors journal 2023-11, Vol.23 (22), p.27324-27330
• Main Authors: Jiang, Chunlei, Dai, Penghui, Li, Xinru, Cong, Zhicheng, Dong, Taiji, Sun, Yu, Liu, Xiankun, Sui, Yuan, Chen, Peng, Yu, Xianli, Wang, Xiufang
• Format: Article
• Language: English
• Subjects: Air flow; Coupling; Diameters; Doping; Empirical analysis; Evanescent field; microfiber sensor; Microfibers; Microspheres; microspheres coupling; Monitoring; Optical fiber sensors; Optical fibers; Optical films; Optical surface waves; Polydimethylsiloxane; respiratory monitoring; self-mixing interferometer; Sensitivity; Sensors; Statistical analysis; Wearable technology
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2023.3319078

We propose a flexible wearable respiratory sensor based on microspheres coupling, where the sensing element is a microfiber embedded in a polydimethylsiloxane (PDMS) film doped with 5- \mu \text{m} -diameter silica microspheres. In this study, PDMS doped with microspheres was used to coat microfibers for the first time, and the enhancement of the evanescent field on the surface of microfibers was observed. Theoretically and experimentally, it is found that the light transmitted in the optical fiber core is effectively dragged by the microsphere, which significantly enhances the evanescent field and thus improves the sensitivity of the sensing element. During the respiratory monitoring, the pressure generated by the respiratory airflow causes the sensing element to bend, and the self-mixing interference is used to detect the power change of reflected light to reconstruct the respiratory signal. The empirical findings demonstrate a peak in sensor sensitivity at a microsphere doping concentration of 0.1 g/mL, while a subsequent augmentation in microspheres doping concentration inversely correlates with sensor sensitivity. Notably, the sensor developed with a 0.1-g/mL microspheres doping concentration exhibits an exceptional capacity for continuous, real-time differentiation among diverse respiratory signals. This innovation is characterized by its elevated sensitivity and responsiveness, evidenced by an impressively short 28-ms response time. To validate the sensor's effectiveness, we employed the Bland-Altman statistical analysis test to assess the accuracy of respiration rate measurements using the collected data from the test subjects. The favorable outcomes we obtained offer a promising avenue for advancing research in the realm of noninvasive vital signs monitoring.