呼吸率是衡量人体健康状况的重要指标之一. 针对现有呼吸率检测方法存在人体受测姿态单一、准确率低和鲁棒性差的问题, 提出适用于多种姿态下的人体呼吸率视觉检测方法. 该方法使用普通摄像机拍摄人体呼吸视频. 首先, 利用图像金字塔光流法处理视频连续图像得到运动前景区域, 将其中最大连通区域初步认定为胸腹呼吸区域. 然后, 将视频每一帧图像的呼吸区域输入复可控金字塔进行多尺度多方向空间分解, 得到多个尺度多个方向的幅度谱和相位谱. 在此基础上将每一帧的多个尺度多个方向相位谱用幅度谱加权后进行平均得到相位-时间信号. 最后, 对提取的信号进行判断, 若信号主频在呼吸信号频带范围内且能量占比高则对该信号通过峰值检测得到呼吸率, 否则重新选取视频连续图像进行后续检测. 实验结果表明, 本文方法适用于人体多种姿态下的呼吸率检测, 在准确率和鲁棒性上优于现有方法.
Respiratory rate is one of the important indicators of human health. To solve the problems of the existing respiratory rate detection methods including one single human posture and poor detection accuracy and robustness, this study proposes a visual detection method of human respiratory rate suitable for multiple postures. This method uses an ordinary camera to capture human breathing videos. The image pyramid optical flow is used to process continuous video images and thereby obtain the moving foreground region, wherein the largest connected area is preliminarily identified as the thoracoabdominal breathing area. Then, the breathing region in each frame of the video is input into the complex steerable pyramid for multi-scale and multi-directional spatial decomposition, and amplitude spectra and phase spectra on multiple scales and in multiple directions are obtained. On this basis, the phase spectra on multiple scales and in multiple directions of each frame are weighted by the amplitude spectra and then averaged to obtain the phase-time signal. Finally, decisions are made for the extracted signal. If the dominant frequency of the signal is within the frequency band of the respiratory signal and the energy proportion is high, the respiratory rate is obtained by peak detection of the signal. Otherwise, continuous video images are reselected for subsequent detection. The experimental results show that this method is suitable for respiratory rate detection in various postures and that it is superior to the existing methods in accuracy and robustness.