Random-Noise Denoising and Clutter Elimination of Human Respiration Movements Based on an Improved Time Window...

Area of Science:

• Biomedical Engineering
• Radar Systems
• Signal Processing

Background:

• Vital signs monitoring is crucial for healthcare.
• Non-contact methods for vital signs detection are desirable.
• Ultra-wideband (UWB) radar offers potential for through-wall sensing.

Purpose of the Study:

• To develop an improved sensing algorithm for vital signs detection using UWB through-wall radar.
• To enhance the accuracy and reliability of respiration movement detection.
• To reduce noise and clutter for better signal quality.

Main Methods:

• Utilized impulse ultra-wideband (UWB) through-wall radar.
• Implemented an improved sensing algorithm for noise de-noising and clutter elimination.
• Employed wavelet packet decomposition and spectral kurtosis for signal analysis and distance estimation.
• Reduced data size using a defined region of interest (ROI).
• Estimated respiration frequency with a multiple time window selection algorithm.

Main Results:

• The proposed filter improved the signal-to-noise ratio (SNR) of vital signs signals.
• The method effectively reduced data size and improved system efficiency.
• Experimental results demonstrated the efficacy and reliability of the vital signs estimation.
• Achieved superior vital signs estimation compared to existing techniques.

Conclusions:

• The developed UWB radar system with an improved algorithm provides accurate and reliable vital signs detection.
• The method offers a promising non-contact solution for monitoring human respiration.
• This technique has the potential to advance remote patient monitoring and surveillance applications.