Respiratory rate estimation on embedded system.
Resumen:
We present the design, implementation, and results of an algorithm for respiratory rate estimation using respiratory induced frequency, intensity, and amplitude variation calculated from the photoplethysmography (PPG) signal. The algorithm was developed in Python (on a PC) using synthesized signals and publicly respiration and PPG available data. Later, we ported it to an MSP432P401R microcontroller. Preliminary results are promissory and show that respiratory rate estimation can be performed on the selected platform. This work also includes a graphical user interface that runs on a PC to process data from sensors, configure alarms and display vital signs in real-time.
| 2022 | |
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Respiratory rate estimation Photoplethysmography Signal processing Low-power embedded system |
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| Inglés | |
| Universidad de la República | |
| COLIBRI | |
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http://www.sase.com.ar/case/about/
https://hdl.handle.net/20.500.12008/33701 |
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| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
