Privacy-Protected Sleep Staging Using Blurred Videos

Cameras hold great potential in sleep monitoring and are suitable for long-term home use. However, privacy invasion is a major concern of cameras in sleep monitoring. A defocused camera offers a promising privacy-protection solution, its feasibility for physiological signal measurement has been shown but its performance on sleep staging remains unknown. We applied four levels of post-blurring (from sharp to blurred videos) to investigate the sleep staging including wakefulness (Wake), rapid eye movement (REM), light stage (Light), and deep stage (Deep). The results showed that all four levels of blurring effectively provide identity protection, but the sleep staging performance (especially the Light) was degraded by video blurring, particularly due to the distorted motion cues and high-frequency components of heart rate variability (HRV). To this end, we introduced Cardiopulmonary Coupling (CPC) to video-based sleep staging. With CPC, the accuracy (ACC) reached 69.5% (kappa = 0.59, F1-score = 0.67) with privacy protection, while under the most severe blurring, ACC was improved from 59.8% (kappa = 0.49, F1-score = 0.56) to 66.9% (kappa = 0.54, F1-score = 0.65). The main benefit of CPC is that the photoplethysmography (PPG) derived respiration (PDR) signal is more robust than inter-beat interval (IBI) under video blurring. Overall, this study explores the opportunity of using blurred videos for privacy-protected sleep staging and demonstrates the effectiveness of CPC in mitigating the degradation of motion and HRV features caused by video blurring. Cohort diversity and multimodal integration are expected to offer deeper clinical and technical insights for real-world applications.