Contactless Respiration Monitoring System Based on Load Under the Bed Legs Considering Postural Changes During Sleep.

Area of Science:

• Biomedical Engineering
• Health Monitoring Technologies
• Geriatric Care Innovation

Background:

• Continuous respiratory rate monitoring is vital for early detection of health deterioration in care facility residents.
• Traditional non-contact systems struggle with accuracy during significant posture or position changes.
• Accurate, non-contact respiratory monitoring is essential for timely medical intervention.

Purpose of the Study:

• To develop a robust non-contact system for continuous respiratory rate measurement.
• To overcome limitations of existing systems in detecting respiratory rates during patient movement.
• To enhance resident safety through reliable, real-time health status monitoring.

Main Methods:

• Utilized Principal Component Analysis (PCA) for feature extraction.
• Analyzed center-of-gravity fluctuations influenced by respiration.
• Developed a non-contact sensing system for bed-based monitoring.

Main Results:

• Successfully extracted respiration-influenced features from center-of-gravity data.
• Demonstrated stable and accurate respiratory rate measurement despite significant posture changes.
• Validated the system's efficacy in non-contact, real-time monitoring.

Conclusions:

• The proposed PCA-based method enables stable, non-contact respiratory rate measurement.
• This technology can significantly improve early health deterioration detection in care facilities.
• The system offers a reliable solution for monitoring residents, especially during positional transitions.