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<p>Respiratory rate is a critical parameter for activating rapid response systems. Given the limitations of existing respiratory rate measurement methods, we aimed to develop a simple, affordable, portable, non-contact, and automatic measurement device using commercially available optical components. We further verified its measurement accuracy through experiments involving a simulator and a volunteer. The proposed system consisted of a webcam with 10 infrared light-emitting diodes, a webcam arm stand, and a laptop. The system employed the law of light attenuation to assess changes in the distance between the camera and the body surface and then extracted depth information from two-dimensional images. In the simulator experiments, the Bland–Altman analysis revealed a bias of 0.167 between simulator settings and automatic system measurements, and 0.200 between simulator settings and visual measurements by a nurse. In the volunteer experiment, the bias between automatic system measurements and visual measurements by a nurse was 0.033. The results were satisfactory. The proposed method exhibits sufficient measurement accuracy for practical use in an individual with a stable respiratory state. Collectively, our findings suggest that the device could reduce observational burden on nurses and significantly improve recording rate of respiratory parameters.</p>

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Development of a Non-contact Respiratory Rate Measurement Method Considering Introduction of Rapid Response Systems

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月29日

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  • Shihoko Kajiwara,
  • Naomi Akiyama,
  • Takahiro Tamaki

摘要

Respiratory rate is a critical parameter for activating rapid response systems. Given the limitations of existing respiratory rate measurement methods, we aimed to develop a simple, affordable, portable, non-contact, and automatic measurement device using commercially available optical components. We further verified its measurement accuracy through experiments involving a simulator and a volunteer. The proposed system consisted of a webcam with 10 infrared light-emitting diodes, a webcam arm stand, and a laptop. The system employed the law of light attenuation to assess changes in the distance between the camera and the body surface and then extracted depth information from two-dimensional images. In the simulator experiments, the Bland–Altman analysis revealed a bias of 0.167 between simulator settings and automatic system measurements, and 0.200 between simulator settings and visual measurements by a nurse. In the volunteer experiment, the bias between automatic system measurements and visual measurements by a nurse was 0.033. The results were satisfactory. The proposed method exhibits sufficient measurement accuracy for practical use in an individual with a stable respiratory state. Collectively, our findings suggest that the device could reduce observational burden on nurses and significantly improve recording rate of respiratory parameters.