Monitoring respiratory state from near-infrared face video images

In this paper, we propose an algorithm for estimating respiratory state using near-infrared facial video images. Estimation of respiratory state is an important indicator for early detection of respiratory diseases. In particular, there is a demand for monitoring respiratory state during the night. One method of monitoring respiratory state is to use contact-type sensors. However, this method requires the installation of many sensors and a visit to a hospital, which place a burden on patients. Therefore, we propose to acquire respiratory-induced features from near-infrared face video images and investigate their similarity to measurements obtained with a respirometer for non-contact monitoring of respiratory state in the dark. Respiratory-induced features were obtained from pulse wave signals extracted from the face video images. The results showed correlations in several respiratory states. This study opens some perspectives in non-contact monitoring of respiratory states.