Benefit of long-wave infrared camera in the measurement of respiratory rate: A pilot study.
Jaeho Kim, Sungho Kim, Sreya Deb Srestha, Uday Debnath, Min Cheol Chang
Abstract
Open AccessThis study evaluated the accuracy of a long-wave infrared camera-based nostril temperature flow method for estimating respiratory rate across different breathing patterns. Five participants (four males and one female; aged between their mid-20s and mid-40s) were monitored using five sensors: a long-wave infrared camera, red-green-blue webcam, red-green-blue camera, respiratory belt, and electrocardiogram sensor. Participants performed regular (17-19 breaths per minute), shallow (32-98 breaths per minute), and deep (5-8 breaths per minute) breathing. The long-wave infrared camera demonstrated the highest accuracy among all devices, with mean absolute errors of 0.6 (regular), 2.4 (shallow), and 0 (deep) breaths per minute. The respiratory belt demonstrated similar performance for regular (0.2 breaths per minute) and deep (0 breaths per minute) breathing; however, it exhibited a significantly higher error (26.0 breaths per minute) during shallow breathing. In contrast, the red-green-blue webcam, red-green-blue camera, and electrocardiogram sensor produced higher mean absolute errors during shallow breathing (44.4, 32.4, and 34.2 breaths per minute, respectively). Overall, the long-wave infrared camera consistently outperformed the other modalities across all breathing patterns, particularly excelling in scenarios with extreme respiratory rates. These findings highlight the long-wave infrared camera's potential for accurate, noncontact respiratory rate monitoring in clinical and remote health settings, particularly where conventional sensors may fail due to motion artifacts or irregular breathing.