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Respiration frequency rate monitoring using smartphone-integrated polymer optical fibers sensors with cloud connectivity.
- Source :
-
Optical Fiber Technology . Jul2023, Vol. 78, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- This paper presents a respiratory frequency system composed by a polymer optical fiber sensor using a smartphone as the interrogator and a remote access to information through a Web server. The system developed a locally-based signal processing method for a dedicated designed application while ensuring remote access using the Thingspeak Web server and application. To check the sensor accuracy, tests with known respiratory rates of 30, 35 and 40 Breaths per Minute (BPM), respectively, are performed using a metronome. The sensor is manually stretched on the metronome beats frequency and the results achieved by the system were of 30.3599, 35.88 and 41.4 BPM. Furthermore, tests are performed in volunteers to check system performance in a real environment, where the volunteers are asked to breathe normally so their respiratory rate could be counted manually and compared to the values delivered by the experimental system in a given period. The error rate verified in the validation experiments are less than 2%. To verify the remote access to information, it is checked whether the respiratory rate data measured by the acquisition system is accordingly sent and visualized by Thingview: the application used in this prototype. The frequency read on the app is the same as measured by the sensor, which shows the suitability of the proposed approach for remote sensing applications with cloud integration. • Local data acquisition using a smartphone and dedicated platform. • Smartphone-integrated optical fiber sensor for real-time respiration monitoring. • Remote Access to information using free web server and application. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10685200
- Volume :
- 78
- Database :
- Academic Search Index
- Journal :
- Optical Fiber Technology
- Publication Type :
- Academic Journal
- Accession number :
- 163551598
- Full Text :
- https://doi.org/10.1016/j.yofte.2023.103313