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Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12008/33701 How cite
Title: Respiratory rate estimation on embedded system.
Authors: Morales, Isabel
Martínez Hornak, Leonardo
Solari, Alfredo
Oreggioni, Julián
Type: Preprint
Keywords: Respiratory rate estimation, Photoplethysmography, Signal processing, Low-power embedded system
Issue Date: 2022
Abstract: 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.
Publisher: CASE
IN: XII Congreso Argentino de Sistemas Embebidos (CASE2022), UNLP, La Plata, Buenos Aires, Argentina, 18-19 ago. 2022, pp. 1-3.
Citation: 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.
License: Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Appears in Collections:Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica

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