Li Shiqi, Wang Haipeng, Liu Yibin
School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Dec 25;38(6):1173-1180. doi: 10.7507/1001-5515.202011029.
Traditional methods of non-contact human respiratory rate measurement usually require complex devices or algorithms. Aiming at this problem, a non-contact respiratory rate measurement method based on only the RGB video information was proposed in this paper. The method consisted of four steps. Firstly, spatial filtering was applied to each frame of the input video. Secondly, a gray compensation algorithm was used to compensate for the gray level change caused by the environmental light. Thirdly, the gray levels of each pixel over time were filtered separately by a low-pass filter. Finally, the region of interest was determined based on the filtering results, and the respiration rate of the human is measured. The physical measurement experiments were designed, and the measurement accuracy was compared with that of the biological radar. The error of the proposed method was between - 5.5% and 3% in different detection directions. The results show that the non-contact respiration rate measurement method can effectively measure the human respiration rate.
传统的非接触式人体呼吸率测量方法通常需要复杂的设备或算法。针对这一问题,本文提出了一种仅基于RGB视频信息的非接触式呼吸率测量方法。该方法包括四个步骤。首先,对输入视频的每一帧进行空间滤波。其次,使用灰度补偿算法来补偿环境光引起的灰度变化。第三,通过低通滤波器分别对每个像素随时间的灰度进行滤波。最后,根据滤波结果确定感兴趣区域,并测量人体的呼吸率。设计了物理测量实验,并将测量精度与生物雷达的测量精度进行了比较。该方法在不同检测方向上的误差在-5.5%至3%之间。结果表明,该非接触式呼吸率测量方法能够有效地测量人体呼吸率。