Respiratory rate detection algorithm based on RGB-D camera: theoretical background and experimental results.

Area of Science:

• Biomedical Engineering
• Computer Vision
• Physiological Monitoring

Background:

• Accurate respiratory rate monitoring is crucial for diagnosing and managing various medical conditions.
• Traditional methods often require physical contact, which can be uncomfortable or impractical in certain scenarios.

Purpose of the Study:

• To develop and validate a novel algorithm for non-contact human respiratory rate measurement.
• To assess the algorithm's performance using depth image sensing techniques.

Main Methods:

• The algorithm utilizes depth image sensing to detect morphological changes in the chest wall.
• It identifies the human chest, calculates its distance from the camera, and analyzes instantaneous distance variations to differentiate breathing from movement.
• Experimental validation involved comparing the algorithm's measurements against a spirometer (gold standard) across five distinct tests.

Main Results:

• The proposed algorithm demonstrated accurate measurement of respiratory rate.
• Performance was evaluated under ideal conditions and varied operating conditions, showing consistent results.
• The system proved to be a viable alternative to invasive sensors for monitoring respiratory activity.

Conclusions:

• The developed algorithm offers a reliable, non-contact method for respiratory rate assessment.
• Depth image sensing provides a promising approach for unobtrusive physiological monitoring.
• This technology presents a practical alternative for continuous respiratory monitoring without physical sensors.