Performance enhancement of thermal image analysis for noncontact cardiopulmonary signal extraction

Abstract

Infrared thermography (IRT) has emerged as a tool for the rapid and non-contact detection of febrile individuals in places of mass gathering. This study explores the feasibility of extracting cardiopulmonary signals (i.e., respiration and cardiac pulse signals) by analyzing thermal image sequences. A high IR spatial resolution (320 × 240 pixels) IRT was applied to acquire facial thermal image sequences at a frame rate of 60 frames per second (fps). The respiration signal was extracted by monitoring the temperature changes in the region of interest (ROI) of the nostrils caused by breathing, that is, the temperature increase during the exhalation phase and the temperature decrease during the inhalation phase. The respiration signal was extracted by picking up the rise and fall motions of the shoulders caused by breathing. The cardiac pulse signal was extracted by measuring tiny head motions accompanying the cardiac cycle on the thermal image sequences. The system was tested on 11 subjects in a laboratory setting to assess the respiration performance and pulse signal extraction. Bland–Altman and Pearson's correlation plots were used to compare the noncontact respiration rate (RR) and pulse rate (PR) measurements with contact-type ECG and respiration belt. The mean difference in the RR was − 0.2 bpm with the 95 % limit of − 5.0 to 4.6 bpm, correlation of 0.83, root mean square error (RMSE) of 2.4 bpm, and mean absolute percentage error (MAPE) of 22 %. Regarding the PR, the mean difference of 4.2 bpm with the 95 % limit of − 18 to 26 bpm, correlation of 0.67, RMSE of 12 bpm, and MAPE of 15 % were determined from comparison of the ECG and thermal camera. In summary, our findings suggest that the proposed thermal image analysis method for measuring RR and PR is promising, particularly for RR measurements. Further validation and refinement are required for the PR measurements. The results indicate that this noncontact approach has potential for various medical applications.