Respiration and heart rates measurement using 77GHz FMCW radar with blind source separation algorithm

Area of Science:

• Signal Processing
• Biomedical Engineering
• Radar Technology

Background:

• Accurate measurement of vital signs like respiration and heartbeat rates is crucial for health monitoring.
• Traditional methods may have limitations in non-contact, continuous monitoring scenarios.
• Frequency Modulated Continues Wave (FMCW) radar offers potential for remote physiological monitoring.

Purpose of the Study:

• To develop and validate a blind source separation-based signal processing method for measuring respiration and heartbeat rates.
• To enhance signal quality using advanced noise reduction techniques for improved accuracy.
• To assess the method's efficacy in separating vital signs for single and multiple individuals.

Main Methods:

• Utilized Frequency Modulated Continues Wave (FMCW) radar operating in the 77GHz-81GHz range.
• Employed Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for signal preprocessing.
• Decomposed phase signals into intrinsic mode functions (IMFs) and reconstructed the signal using selected IMFs.

Main Results:

• Achieved accurate separation of respiration and heartbeat signals for a single person with average deviations of 1.1 bpm and 6.8 bpm, respectively.
• Successfully demonstrated the separation of respiratory signals for two distinct individuals.
• The CEEMDAN method significantly improved the quality and separability of the radar-detected vital signs.

Conclusions:

• The proposed blind source separation method combined with CEEMDAN and FMCW radar provides a robust and accurate approach for non-contact vital sign monitoring.
• This technique shows promise for applications requiring the simultaneous measurement of respiration and heartbeat rates, even in complex scenarios with multiple subjects.
• Future work could explore further optimization and real-world clinical validation of this radar-based system.