Non-contact breathing rate monitoring system using a magnification technique and artificial hydrocarbon networks

Jorge Brieva; Hiram Ponce; Ernesto Moya-Albor

doi:10.1117/12.2580077

3 November 2020 Non-contact breathing rate monitoring system using a magnification technique and artificial hydrocarbon networks

Jorge Brieva, Hiram Ponce, Ernesto Moya-Albor

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Proceedings Volume 11583, 16th International Symposium on Medical Information Processing and Analysis; 115830R (2020) https://doi.org/10.1117/12.2580077
Event: The 16th International Symposium on Medical Information Processing and Analysis, 2020, Lima, Peru

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%.

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Jorge Brieva, Hiram Ponce, and Ernesto Moya-Albor "Non-contact breathing rate monitoring system using a magnification technique and artificial hydrocarbon networks", Proc. SPIE 11583, 16th International Symposium on Medical Information Processing and Analysis, 115830R (3 November 2020); https://doi.org/10.1117/12.2580077

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KEYWORDS

Video

Molecules

Motion estimation

Data modeling

Error analysis

Image processing

Beam propagation method

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