基于视觉的非接触呼吸频率自动检测方法

Vision-based automatic detection method for non-contact respiratory rate

针对生理健康监测领域的呼吸率检测舒适度及效率问题,提出了一种基于视觉的非接触式测量方法,该方法利用普通相机拍摄人体呼吸视频,并通过欧拉算法将呼吸时的胸腹运动位移加以放大,考虑人体胸腹区域位置提取准确度对呼吸率检测精度的影响,提出了基于光流信号提取呼吸区域的方法,利用光流算法将胸腹运动转化为光流信息并进行编码,将其显示为彩色图像形式,从中提取胸腹呼吸区域的像素亮度序列,从而得到呼吸波形信息,通过波峰检测获取呼吸率。最后,实验将本算法自动提取的呼吸信号与Embla N7000多导睡眠仪测量结果相比较,结果表明,本算法呼吸率检测平均误差为0.54次/min,具有较高的准确性。

Aiming at the comfort and efficiency problems of respiratory rate detection in the field of physiological health monitoring,this paper proposes a vision-based non-contact measurement method,which uses a common camera to capture the human respiratory video and enlarges the displacement of the chest and abdomen motion during breathing with Euler algorithm.Considering the influence of the position extraction accuracy of the chest and abdomen area on the accuracy of the respiratory rate detection,this paper proposes a method based on optical flow signal to extract the respiratory region.The optical flow algorithm is used to convert the chest and abdomen motion into optical flow information,which are encoded and displayed in the form of a color image.The pixel brightness sequence of the chest and abdomen breathing region is extracted to obtain respiratory waveform information,and the respiratory rate is obtained with peak detection.Finally,experiment was conducted,and the breath signals extracted using the proposed algorithm were compared with the measurement results using Embla N7000 polysomnography.The results show that the average error of respiratory rate detected with the proposed algorithm is 0.54 times/min,which has high accuracy.