Analysis of the correlation between infrared thermal sequence images of nostril area and respiratory rate. Issue 13 (7th October 2020)

• Record Type: Journal Article
• Authors: Jian, Bo‐Lin; Huang, Min‐Wei; Lee, Shin‐Hsiung; Yau, Her‐Terng
• Is Part Of: IET image processing. Volume 14:Issue 13(2020)
• Page Start: 3089
• Page End: 3094
• Publication Date: 2020-10-07
• Subjects: medical image processing -- pneumodynamics -- image sequences -- biomedical optical imaging -- infrared imaging -- image filtering -- least squares approximations -- spectral analysis -- independent component analysis; facial thermal image information -- region selection -- thermal image sequence data calibration -- Hampel filter -- independent component method -- nonrespiratory signals -- Savitzky‐Golay filtering -- signal baseline -- standard abdominal breathing band signals -- spectral coherence analysis -- respiratory signals -- infrared thermal sequence images -- respiratory rate -- breathing rate -- least squares method -- nostril region thermal image signals -- normal respiratory frequency range -- MVAR model -- frequency 0.1 Hz to 0.5 Hz -- frequency 0.15 Hz to 0.2 Hz; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2019.0416
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : 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.