# A Real-Time Remote Respiration Measurement Method with Improved Robustness Based on a CNN Model
## 2 Related Works
### Motion-Based Respiration Measurement Method  
Respiration can also be measured using a noncontact method in which an RGB camera is used to quantitatively detect minute movements of the human body, such as expansion and contraction of the chest caused by respiration. As shown in Figure 1, changes such as the diaphragm moving up and down during breathing, the external intercostal muscles pulling up the ribs and expanding, and the volume of the chest cavity increasing, cause the upper body to move overall [51]. Studies were conducted to measure respiration in a noncontact manner by quantitatively measuring such changes in chest movement. [PERSON] et al. detected the approximate position of the upper body using the Haar-like feature-based object detection method [52] proposed by [PERSON] and [PERSON] in 2013, and defined body regions as RoIs based on the position of the face to estimate respiration rate by applying frequency analysis techniques to the average change in brightness of a time-series signal within the RoI [53]. Similarly, in 2016, [PERSON] et al. captured images of the abdomen of the human body using a camera on an Android smartphone and estimated respiration information using the average changes in the pixels of the images [54,55]. [PERSON] et al. proposed a method to measure respiration by tracking changes in reflected light using the principle that changes caused by respiratory movement change the light reflected from the chest wall [56]. [PERSON] et al. conducted a study to compare the respiration information measured by the average pixel change obtained from RoIs with a reference by selecting the boundary region of the RoI [57]. Although these studies showed that movement caused by respiration can be optically observed, several challenges remain to be solved before these methods can be universally adopted. Estimating motion information by simply using the amount of pixel change is simple to implement, and the computational cost is very low. Figure 2 shows examples of different pixel variation signals that can be observed with the same respiration periods. The scale of the pixel value also varies greatly depending on color changes, and Figure 2 shows that the normalized signal clearly confirms these trends. As may be observed from Figure 2, the pixel variation signal may have a different phase from the actual respiration signal owing to numerous factors, such as the subject's clothes, background, and lighting. In addition, this change may exhibit a completely different periodicity from breathing movement in some cases. These factors can significantly degrade the performance of respiration motion estimation methods based on the amount of change in pixels, and act as a limit that renders detecting the exact timing of inspiration and expiration through motion information impossible. [PERSON] et al. and [PERSON] et al. used Eulerian video magnification [58], a technique for amplifying small movements with periodicity, to amplify movement by respiration and then to amplify the difference between adjacent frames [59,60]. However, these methods also perform amplification based on the amount of pixel change; therefore, they are subject to the limitations of pixel change-based methods. To quantitatively measure movement driven by respiration, an optical flow method was used to calculate the movement speed of a specific pixel pattern in an image [61]. Because optical flow estimates a motion vector owing to movement, it can mitigate some problems of methods that simply measure the amount of change in the pixels. In 2016, [PERSON] et al. estimated the relative position of body regions through face detection and measured respiration by calculating the movement of the body regions as an optical flow [62]. In 2018, [PERSON] et al. estimated body RoIs using a depth camera, mapped the image acquired with an RGB camera, and then applied optical flow to the RoI to measure respiration [63]. [PERSON] et al.