Breathing is one of the vital signs used to assess the physical health of a subject. Non-contact-based measurements of both breathing rate and changes in breathing rate help monitor health condition of subjects more flexibly. In this paper, we present an improved real-time camera-based adaptive breathing monitoring system, which includes real time (1) adaptive breathing motion detection, (2) adaptive region of interest detection to eliminate environmental noise, (3) breathing and body movement classification, (4) respiration rate estimation, (5) monitor change in respiration rate to examine overall health of an individual, and (6) online adaptation to lighting. The proposed system does not pose any positional and postural constraint. For evaluation, 30 videos of 15 animals are tested with drugs to simulate various medical conditions and breathing patterns, and the results from the proposed system are compared with the outputs of an existing FDA-approved invasive medical system for patient monitoring. The results show that the proposed method performs significantly correlated RR results to the reference medical device with the correlation coefficient equal to 0.92 and p-value less than 0.001, and more importantly the proposed video-based method is demonstrated to produce alarms 10 to 20 s earlier than the benchmark medical device.

呼吸是用于评估受试者身体健康的生命体征之一。呼吸频率和呼吸频率变化的非接触式测量有助于更灵活地监测受试者的健康状况。在本文中，我们提出了一种改进的基于实时摄像头的自适应呼吸监测系统，包括实时（1）自适应呼吸运动检测，（2）自适应感兴趣区域检测以消除环境噪声，（3）呼吸和身体运动分类，（4）呼吸率估计，（5）监测呼吸率变化以检查个人的整体健康状况，以及（6）在线适应照明。所提出的系统不构成任何位置和姿势约束。为了评估，用药物对 15 只动物的 30 个视频进行了测试，以模拟各种医疗条件和呼吸模式，并将拟议系统的结果与现有 FDA 批准的用于患者监测的侵入性医疗系统的输出进行比较。结果表明，所提出的方法与参考医疗器械具有显着相关的 RR 结果，相关系数等于 0.92，p值小于 0.001，更重要的是，所提出的基于视频的方法被证明比基准医疗设备早 10 到 20 秒产生警报。