Key result
Near-infrared face video yields ~0.72 correlation with pulse wave meters and detects normal breathing states.
Why the study?
Monitoring respiratory state typically requires contact-type sensors and hospital visits, creating patient burden, especially for monitoring in the dark.
Near-infrared facial video imaging can estimate normal, deep, and shallow breathing states, though apnea detection remains challenging and requires further refinement to accommodate facial motion.
Non-contact NIR video may enable remote pulse and breathing assessment; leaves open reliable apnea detection pending larger validation.
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.
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Ashida et al. (2024) studied Respiratory state monitoring (n=3). Near-infrared face video image-based respiratory monitoring vs. Contact-type respirometer was evaluated on Correlation coefficient between estimated pulse wave signals and pulse wave meter measurements. Near-infrared face video image analysis extracted pulse wave signals that correlated highly with a pulse wave meter (r = 0.72) and detected normal and deep breathing states, though apnea detection was less accurate.
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