Respiratory rate estimation on embedded system.

 

Autor(es):
Morales, Isabel ; Martínez Hornak, Leonardo ; Solari, Alfredo ; Oreggioni, Julián
Tipo:
Preprint
Versión:
Enviado
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.

Año:
2022
Idioma:
Inglés
Temas:
Respiratory rate estimation
Photoplethysmography
Signal processing
Low-power embedded system
Institución:
Universidad de la República
Repositorio:
COLIBRI
Enlace(s):
http://www.sase.com.ar/case/about/
https://hdl.handle.net/20.500.12008/33701
Nivel de acceso:
Acceso abierto