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Respiratory rate detection algorithm based on RGB-D camera: theoretical background and experimental results

机译:基于RGB-D摄像机的呼吸频率检测算法:理论背景和实验结果

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摘要

Both the theoretical background and the experimental results of an algorithm developed to perform human respiratory rate measurements without any physical contact are presented. Based on depth image sensing techniques, the respiratory rate is derived by measuring morphological changes of the chest wall. The algorithm identifies the human chest, computes its distance from the camera and compares this value with the instantaneous distance, discerning if it is due to the respiratory act or due to a limited movement of the person being monitored. To experimentally validate the proposed algorithm, the respiratory rate measurements coming from a spirometer were taken as a benchmark and compared with those estimated by the algorithm. Five tests were performed, with five different persons sat in front of the camera. The first test aimed to choose the suitable sampling frequency. The second test was conducted to compare the performances of the proposed system with respect to the gold standard in ideal conditions of light, orientation and clothing. The third, fourth and fifth tests evaluated the algorithm performances under different operating conditions. The experimental results showed that the system can correctly measure the respiratory rate, and it is a viable alternative to monitor the respiratory activity of a person without using invasive sensors.
机译:同时介绍了开发用于无需任何物理接触即可进行人类呼吸频率测量的算法的理论背景和实验结果。基于深度图像传感技术,通过测量胸壁的形态变化来得出呼吸频率。该算法识别人的胸部,计算其与摄像头的距离,并将该值与瞬时距离进行比较,从而识别出这是由于呼吸作用还是由于被监视人员的活动受限而引起的。为了实验上验证所提出的算法,将来自肺活量计的呼吸频率测量值作为基准,并将其与算法估算的值进行比较。进行了五次测试,五个不同的人坐在镜头前。第一个测试旨在选择合适的采样频率。进行了第二次测试,以比较建议的系统在理想的光线,方向和衣服条件下相对于金标准的性能。第三,第四和第五次测试评估了不同操作条件下的算法性能。实验结果表明,该系统可以正确地测量呼吸频率,它是不使用侵入式传感器来监测人的呼吸活动的可行替代方案。

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