J Opt Soc Am A Opt Image Sci Vis. 2020 Nov 1;37(11):C118-C124. doi: 10.1364/JOSAA.399284.
A contact-free inexpensive measurement system with an algorithm based on the integral form of video frames is proposed to estimate the respiration rate from an extracted respiration pattern. The proposed algorithm is applied and tested on 28 videos of sleeping-simulated positions, and the results are compared with the manual visual inspection values. With linear regression, the determination coefficient () is 0.961, which demonstrates high agreement with reference measurements. In addition, the Bland-Altman plot shows that almost all data points are within the 95% limits of agreement. Moreover, the time complexity of the proposed algorithm, which involves taking just a single point value of the integral image, is lower than that of traditional methods that circulate over a large number of points. In other words, the proposed algorithm achieves (1) fixed-time complexity compared to () for traditional methods. The average speed of processing is enhanced by about 17.4%.
提出了一种基于视频帧积分形式的无接触、低成本测量系统，通过提取呼吸模式来估计呼吸率。该算法应用于 28 个模拟睡眠姿势的视频，并将结果与手动视觉检查值进行比较。通过线性回归，确定系数（）为 0.961，与参考测量值高度一致。此外，Bland-Altman 图表明，几乎所有数据点都在 95%一致性限内。此外，该算法的时间复杂度仅涉及积分图像的单个点值，低于传统方法需要循环大量点的复杂度。换句话说，与传统方法相比，该算法实现了（1）固定时间复杂度。处理速度的平均提高了约 17.4%。
