Patient Posture-Adaptive Non-Contact Respiratory Rate Measurement Inside a Moving Ambulance Using RGB and Thermal Cameras

Abstract

Background/Objectives: Monitoring and evaluating respiratory rate (RR) plays a critical role during emergency transport. Conventional RR measurement methods have primarily relied on electrocardiogram-based approaches, which are susceptible to large errors caused by patient body movement and impose a burden on patients due to their contact-based nature. This study aimed to develop a non-contact RR measurement method using RGB and thermal cameras that can be applied inside a moving ambulance. Methods: One of the key challenges in non-contact RR measurement inside an ambulance is accommodating changes in patient posture. We addressed this by patient posture-adaptive automatic image registration between RGB and thermal cameras and developing a nostril detection method robust to posture changes. Results: The image registration error of the proposed method was evaluated at various distances from the camera, and the error was confirmed to remain within 1 pixel. RR measurement experiments simulating various respiratory conditions were then conducted inside a moving ambulance. The average of mean absolute error (MAE) was 0.95, 0.59, and 2.80 breaths per minute (breaths/min) for bradypnea, normal, and tachypnea, respectively, in the supine position, and 1.08, 1.90, and 4.38 breaths/min, respectively, in the semi-sitting position. Evaluation of the proposed nostril detection method further confirmed improved RR estimation accuracy compared with the conventional method. Conclusions: This study achieved patient posture-adaptive automatic image registration and robust nostril detection and successfully conducted experiments under realistic and challenging conditions, representing a substantial step toward the real-world implementation of a non-contact RR measurement system in ambulances.