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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: | Estimation, Microcontrollers, Signal processing algorithms, Embedded systems, Biomedical monitoring, Performance evaluation, Graphical user interfaces, Respiratory rate estimation, Photoplethysmography, Signal processing, Low-power embedded system |
| Fecha de publicación: | 2023 |
| 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 infrared (IR) channel of the SEN-15219 board for photoplethysmography (PPG) acquisition. First, the algorithm was developed in Python (on a PC) using synthetic signals and publicly available respiration and PPG data. We also include a graphical user interface to process data from sensors and display vital signs. Later, we ported the algorithm to an MSP432P401R microcontroller to complete our wearable prototype. Results are promissory and show that respiratory rate estimation can be performed on the selected platform with our proposed Fourier Product (FP) method, which results in a Mean Absolute Error of 4.1 using 16-seconds windows of IR-PPG signals. |
| Descripción: | Los autores desean agradecer al Núcleo de Ingeniería Biomédica, la Comisión Sectorial de Investigación Científica (CSIC, UdelaR) y al capítulo uruguayo de la IEEE Circuits and Systems Society. Publicado en IEEE Embedded Systems Letters, 2023. |
| Financiadores: | Este trabajo fue parcialmente financiado por CSIC, Universidad de la República, Uruguay |
| Citación: | Morales, I., Martínez Hornak, L., Solari, A. y otros. Respiratory rate estimation on embedded system. [Preprint]. Publicado en: IEEE Embedded Systems Letters. 2023. DOI: 10.1109/LES.2023.32793622023. |
| Licencia: | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
Ficheros en este ítem:
| Fichero | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| MMSO23.pdf | Preprint | 836,19 kB | Adobe PDF | Visualizar/Abrir |
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