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| Título: | Respiratory rate estimation on embedded system. |
| Autor: | Morales, Isabel Martínez Hornak, Leonardo Solari, Alfredo Oreggioni, Julián |
| Tipo: | Preprint |
| Palabras clave: | Respiratory rate estimation, Photoplethysmography, Signal processing, Low-power embedded system |
| Fecha de publicación: | 2022 |
| 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. |
| Editorial: | CASE |
| EN: | XII Congreso Argentino de Sistemas Embebidos (CASE2022), UNLP, La Plata, Buenos Aires, Argentina, 18-19 ago. 2022, pp. 1-3. |
| Citación: | Morales, I., Martínez Hornak, L., Solari, A. y otros. Respiratory rate estimation on embedded system [Preprint]. Publicado en: XII Congreso Argentino de Sistemas Embebidos (CASE2022), UNLP, La Plata, Buenos Aires, Argentina, 18-19 ago. 2022, pp. 1-3. |
| Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
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