Non-contact breathing rate monitoring system using a magnification technique and artificial hydrocarbon networks
Journal
16th International Symposium on Medical Information Processing and Analysis
Date Issued
2020
Type
text::conference output::conference proceedings::conference paper
Abstract
In this paper, we present a new non-contact strategy to estimate the breathing rate based on the Eulerian motion video magnification technique and an Artificial Hydrocarbon Networks (AHN) as classifier. After the magnification procedure, a AHN is trained to detect the inhalation and exhalation frames in the video. From this classification, the respiratory rate is estimated. The magnification procedure was carried out using the Hermite decomposition. The respiratory rate (RR) is estimated from the classified frames. We have tested the method on 10 healthy subjects in different positions. To compare performance of methods to respiratory rate the mean average error and a Bland and Altman analysis is used to investigate the agreement of the methods. The mean average error for our strategy is 4.46 ± 3.68% with and agreement with respect of the reference of ˜ 98 %. © 2020 SPIE
How to cite
Brieva, J., Ponce, H., & Moya-Albor, E. (2020). Non-contact breathing rate monitoring system using a magnification technique and artificial hydrocarbon networks. 16th International Symposium On Medical Information Processing And Analysis, 115830R (3 November 2020). https://doi.org/10.1117/12.2580077