Open AccessAnalysis of the correlation between infrared thermal sequence images of nostril area and respiratory rate
Author(s) -
Jian BoLin,
Huang MinWei,
Lee ShinHsiung,
Yau HerTerng
Publication year - 2020
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2019.0416
Subject(s) - nostril , smoothing , coherence (philosophical gambling strategy) , mathematics , filter (signal processing) , respiratory rate , calibration , artificial intelligence , computer science , computer vision , statistics , medicine , heart rate , surgery , blood pressure , radiology , nose
In this study, a thermal imaging instrument was used to obtain facial thermal image information which was then used to calculate the number of breaths taken. However, small movements were inevitable and the first issue addressed was the means by which image calibration and region selection was to be made. To this end, thermal image sequence data calibration was done using technology that resolved small natural deviations in the nostril area. After these problems had been solved, a Hampel filter was used to process the nostril area signals. The independent component method was used to filter the effects of non‐respiratory signals, and the least squares method was employed for smoothing. Savitzky‐Golay filtering was used to adjust the signal baseline and the processed nostril region thermal image signals were compared with standard abdominal breathing band signals. Results showed that the difference in the number of breaths per minute was less than 1.5 times. The usual normal respiratory frequency range lies within a range of 0.1–0.5Hz. In the calculation of ‘coherence obtained from MVAR model’, the spectral coherence analysis results showed the methods proposed in this study can substantially enhance the relevance between 0.15 and 0.2Hz.