Rene Gonzalez-Fernandez*, Jose L Hernandez-Caceres and Jorge G Perez-Blanco

Department of Medical Electronic, Cuban Center for Neurosciences, Cuba

*Corresponding Author: Rene Gonzalez-Fernandez, Department of Medical Electronic, Cuban Center for Neurosciences, Cuba.

Received: February 01, 2022; Published: March 03, 2022

Abstract

The aim of this paper is to discuss an approach to the monitoring of respiratory diseases based on the combined study of heart rhythm, respiratory rate and pulse oximetry (SpO2). Respiratory diseases can arise from pulmonary, cardiovascular and other causes, and can be fatal. Worldwide, 235 million people have asthma and 64 million suffer from Chronic Obstructive Pulmonary Disease (COPD). The respiratory system works in coordination with the cardiovascular system and respiratory insufficiencies are compensated by an increase in heart rate, which can lead to heart disorders. The combined study of both systems would allow to know accurately how a respiratory patient evolves. A prototype was developed based on the E305654 module, which on-demand delivers SpO2, photoplethysmography signal samples and pulse rate values, and the STM32L073CZTx processor. A vector was computed every thirty minutes; it is composed by respiratory rate, derived from metrics calculated from the plethysmography signal (PPG), the SpO2 mean value and the pulse rate. 10 healthy volunteers and 6 people with COPD, including one suffering COVID-19, and three asthmatics were studied. The dispersion inside each patient´s group was not significant, but a remarkable difference can be observed between the healthy volunteers and the other studied persons. A “normal region” can be defined with clearly defined frontiers. The proposed solution seems promising to assess respiratory function even when it is compensated by a cardiac response.

Keywords: Respiratory Disease Monitoring; Pulse Oximetry; PPG Signal; PPG Derived Respiratory Rate; Analysis of Chronic Obstructive Pulmonary Disease

References

1. World Health Organization. The World Health Report (2020).
2. Zhu N., et al. “A novel coronavirus from patients with pneumonia in China, 2019”. The New England Journal of Medicine8 (2020): 727-733.
3. Carlos WG., et al. “Novel Wuhan (2019-nCoV) coronavirus”. American Journal of Respiratory and Critical Care Medicine 4 (2020): 7-8.
4. Sepp VP., et al. “Assessment of breathing parameters during running with a wearable bioimpedance device”. 4^th European Conference of the International Federation for Medical and Biological Engineering. Springer Berlin Heidelberg (2009).
5. Karlen W., et al. “Multi-parameter respiratory rate estimation from the photoplethysmogram”. Biomedical Engineering, IEEE Transactions on 60.7 (2013): 1946-1953.
6. Leonard PA., et al. “A fully automated algorithm for the determination of respiratory rate from the photoplethysmogram”. Journal of Clinical Monitoring and Computing1 (2006): 33-36.
7. PH Charlton., et al. “Waveform analysis on estimate respiratory rate". in Secondary Analysis of Electronic Health Records. Springer International Publishing 26 (2016): 377-390.
8. PH Charlton., et al. “Extraction of respiratory signals from the electrocardiogram and photoplethysmogram: technical and physiological determinants". in Physiological Measurements 5 (2017): 669-690.
9. DJ Meredith., et al. “Photoplethysmographic derivation of respiratory rate: a review of relevant physiology”. Journal of Medical and Technology 1 (20012): 1-7.
10. Madhav KV., et al. “Estimation of respiration rate from ECG, BP and PPG signals using empirical mode decomposition”. In Instrumentation and Measurement Technology Conference (I2MTC) IEEE (2011): 1-4.
11. A Fusco., et al. “On how to extract breathing rate from PPG signal using wearable devices”. IEEE Biomedical Circuits and Systems Conference (BioCAS) (2015): 1-4.
12. Goldberger AL., et al. “PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals”. Circulation23 (2000): e215-e220.

Citation

Citation: Rene Gonzalez-Fernandez., et al. “Respiratory Diseases follow-up based on the Extraction of Plethysmography Signal Parameters". Acta Scientific Nutritional Health 6.4 (2022): 02-06.

Copyright

Copyright: © 2022 Rene Gonzalez-Fernandez., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.