A vital signs denoising algorithm for FMCW radar based on BKA-VMD combined wavelet threshold
ID：18
Submission ID：18 View Protection：ATTENDEE
Updated Time：2024-10-23 10:40:28
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Oral Presentation
Start Time：2024-11-02 09:50 （Asia/Shanghai）
Duration：20min
Session：[P5] Parallel Session 5 » [P5-2] Parallel Session 5（November 2 AM）
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Abstract
FMCW radar has excellent ranging and velocity measurement capabilities, combining the velocity resolution of CW radar with the range resolution of UWB radar, and possesses strong anti-interference ability. It does not require contact with any electrodes or sensors when working, offering strong penetration and good privacy. This enables the detection of human vital signs information from a long distance, making it highly valuable for non-contact vital signs detection. But during detection, the chest displacements caused by respiration and the heartbeat is relatively small, besides heartbeat signals can be easily interfered by respiratory harmonics and other noises. A denoising method combining Black-winged Kite Algorithm (BKA) optimized Variational Mode Decomposition (VMD) algorithm and wavelet threshold denoising is introduced for the first time on the issue. Experimental results indicate that when the SNR is 0, the algorithm is compared and analyzed with the EMD joint wavelet thresholding algorithm ，the correlation coefficient improves by 4.36%, the signal-to-noise ratio improves by 5.342dB, and the root-mean-square reduces by 0.7606, which retains more vital signs information while having higher signal-to-noise ratio, and it can be effectively used in the field of vital signs detection.
Keywords
BKA, FMCW radar, VMD, Vital signs signal, Wavelet threshold denoising
Speaker
XieMin
Ms. Xidian UniversitySubmission Author
All comments
15th August 2024 31st August 2024- Manuscript Submission
15th September 2024 - Acceptance Notification
1st October 2024 - Camera Ready Submission
1st October 2024 – Early Bird Registration
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