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 0.1–0.5   Hz. 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 0.2   Hz.

中文翻译：

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鼻孔区红外热像图与呼吸频率的相关性分析

在这项研究中，使用热成像仪获取面部热图像信息，然后将其用于计算呼吸次数。但是，小的移动是不可避免的，要解决的第一个问题是进行图像校准和区域选择的方法。为此，使用解决了鼻孔区域小自然偏差的技术进行了热图像序列数据校准。解决了这些问题之后，使用了Hampel滤波器来处理鼻孔区域信号。独立分量法用于过滤非呼吸信号的影响，最小二乘法用于平滑。使用Savitzky-Golay滤波来调整信号基线，并将处理后的鼻孔区域热图像信号与标准腹部呼吸带信号进行比较。结果表明，每分钟呼吸次数的差异小于1.5倍。通常的正常呼吸频率范围是0.1-0.5   赫兹。在计算“从MVAR模型获得的相干性”时，光谱相干分析结果表明，本研究中提出的方法可以大大增强0.15和0.2之间的相关性。   赫兹。