Paper
26 September 2013 Real-time detection of respiration rate with non-contact mode based on low-end imaging equipment
Xiaoli Jin, Liquan Dong, Yuejin Zhao, Xiaohua Liu, Ming Liu, Lei Yang, Weiyu Liu, Jingsheng Zhao, Jinhui Xing
Author Affiliations +
Abstract
Standard instrumentation for the assessment of respiration rate is large and based on invasive method, and not suitable for daily inspection. An optical, simple and non-contact measurement method to detect human respiration rate using lowend imaging equipment is discussed. This technology is based on the visible light absorption of blood, which contains many important physiological information of the cardiovascular system. The light absorption of facial area can be indirectly reflected to gray value of the corresponding area image. In this paper, we acquire the respiration rate through the video signal captured by low-end imaging equipment. Firstly, the color CCD captures the facial area below the eyes and every frame of the video can be separated into three RGB channels. The blue channel is extracted as the research object. Then, we calculate the mean gray value for each image and draw the mean gray curve along the time. Fourier transform can get the frequency spectrogram of the graph, which is filtered through the Fourier filter. The extreme point is the value of the respiratory rate. Finally, an available interface program is designed and we have some volunteers tested. The correlation coefficient between the experimental data and the data provided by a reference instrument is 0.98. The consistency of the experimental results is very well. This technology costs so low that it will be widely used in medical and daily respiration rate measurement.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaoli Jin, Liquan Dong, Yuejin Zhao, Xiaohua Liu, Ming Liu, Lei Yang, Weiyu Liu, Jingsheng Zhao, and Jinhui Xing "Real-time detection of respiration rate with non-contact mode based on low-end imaging equipment", Proc. SPIE 8856, Applications of Digital Image Processing XXXVI, 88561U (26 September 2013); https://doi.org/10.1117/12.2022147
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KEYWORDS
Video

Blood

MATLAB

Absorption

Doppler effect

Fourier transforms

Independent component analysis

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