Video-based cardiopulmonary coupling measurement: A feasibility study

Cardiopulmonary coupling (CPC) analysis quantifies the synchronization between heart rate variability and respiratory signals to reveal cardiopulmonary interactions, playing an important role in clinical diagnosis and health management. However, traditional CPC methods rely on contact-based sensors, which have the disadvantages of low comfort, limited applicability, and infection risks. To address these limitations, this study proposes a video-based remote CPC measurement method. The approach first identifies and segments facial and thoracoabdominal regions of interest and then fuses multiregional signals to enhance the quality of noncontact cardiopulmonary signals. A continuous wavelet transform (CWT)-based CPC analysis is subsequently employed to improve the time-frequency resolution of the nonstationary physiological signals. Experiments were conducted on a self-collected and publicly available long-term video dataset known as LTHRV. The results show that the video-based CWT-CPC method is highly consistent with contact-based measurements. In both the normal breathing scenario and the apnoea scenario, most Pearson’s correlation coefficients for CPC frequency-domain metrics exceeded 0.6, demonstrating their robustness under varying respiratory conditions. This study confirms the feasibility of video-based CPC measurement and effectively expands the application scope of noncontact physiological monitoring.