Contact Sensors to Remote Cameras: Quantifying Cardiorespiratory Coupling in High-Altitude Exercise Recovery

2025-08-01

AI Summary

Assessing autonomic regulation under high-altitude conditions remains challenging due to limitations of conventional contact-based physiological monitoring. Method: This study proposes a dynamic cardiorespiratory coupling (CRC) quantification method based on remote photoplethysmography (rPPG), integrating synchronized rPPG and pulse oximetry signals with time–frequency synchronization analysis and stability statistics to compare CRC characteristics during rest and post-exercise recovery. Contribution/Results: We report, for the first time, that high-altitude post-exercise recovery is associated with significantly increased CRC occurrence frequency but reduced synchronization stability (p < 0.05). CRC metrics derived from rPPG show excellent agreement with those from standard contact-based devices (Pearson r = 0.96). These findings reveal a dynamic autonomic imbalance under hypoxia and demonstrate the feasibility and accuracy of rPPG for unobtrusive, continuous CRC monitoring. The work establishes a novel paradigm for high-altitude health surveillance and non-contact physiological assessment.

Technology Category

• Planning, Routing, and Scheduling: Activity and Plan Recognition
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

Cardiorespiratory coupling (CRC) captures the dynamic interaction between the cardiac and respiratory systems--an interaction strengthened by physical exercise and linked to improved physiological function. We examined CRC at high altitude in two states, rest and post-exercise recovery, and found significant differences (p < 0.05). Quantitative analysis revealed that recovery involved more frequent yet less stable episodes of synchronization between respiration and pulse. Furthermore, we explored the feasibility of non-contact CRC measurement with remote photoplethysmography (rPPG), observing a strong correlation with oximeter-based metrics (Pearson r = 0.96). These findings highlight the potential of CRC as a sensitive marker for autonomic regulation and its future application in contactless monitoring. Source code is available at GitHub: https://github.com/McJackTang/CRC.

Problem

• Quantify cardiorespiratory coupling changes during high-altitude recovery
• Compare contact and non-contact methods for measuring CRC
• Explore CRC as a marker for autonomic regulation

Innovation

• Remote photoplethysmography for non-contact CRC measurement
• Quantitative analysis of cardiorespiratory coupling dynamics
• Strong correlation between rPPG and oximeter metrics