Radar Vital Sign Monitoring With Adaptive Harmonic Frequency Estimation
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Solution Overview
Problem
Existing radar-based vital sign monitoring systems face challenges in accurately estimating heart rate due to interference from breathing harmonics, background noise, and body movements, leading to unreliable heart rate estimation, especially when the subject is not static and at varying distances from the radar.
Innovation Solution
A radar sensor system using an adaptive Nonlinear Least Squares (NLS) method with individual search regions for each harmonic, combined with frequency estimation techniques like DFT and Kalman filtering, to accurately identify fundamental frequencies of breathing and heartbeat motions, even in dynamic conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If radar-based phase analysis is used to monitor vital signs, then contactless monitoring is achieved, but heartbeat signal detection becomes unreliable due to interference from breathing harmonics and body movements
Solution Approach 1:
The patent segments the heartbeat signal detection by utilizing higher-order harmonics (2nd, 3rd, 4th harmonics) separately from the fundamental frequency. Each harmonic is processed independently through individual NLS estimations, allowing the system to isolate heartbeat information from breathing interference that primarily affects the fundamental frequency region.
Solution Approach 2:
The patent transitions from analyzing only the fundamental frequency dimension to analyzing multiple harmonic dimensions. By examining the 2nd, 3rd, and 4th harmonics of the heartbeat signal, the system accesses additional frequency dimensions where heartbeat information can be distinguished from breathing harmonics, thereby improving detection reliability in contactless mode.
2Measurement precision
If higher-order harmonics of heartbeat are used for estimation, then heart rate accuracy improves, but signal-to-noise ratio requirements increase and tracking becomes sensitive to background noise
Solution Approach 1:
The patent merges information from multiple harmonics (2nd, 3rd, 4th) through individual NLS estimations and combines these estimates to produce a final heartbeat frequency determination. This combining approach allows the system to achieve accurate heart rate estimation while being less sensitive to noise in any single harmonic, effectively reducing the SNR requirement compared to using only higher-order harmonics.
Solution Approach 2:
The patent changes the estimation parameters by applying individual Nonlinear Least Squares (NLS) estimations to each harmonic component rather than treating them uniformly. This parameter-level differentiation allows optimal extraction of heartbeat information from each harmonic while filtering out noise, thereby improving measurement precision without excessively increasing SNR requirements.
3Measurement precision
If conventional DFT and harmonic-based estimation are used, then heart rate can be estimated, but the method only works when the subject is static and within 80 cm distance
Solution Approach 1:
The patent implements dynamics by applying individual NLS estimations that can adapt to time-varying conditions. The system processes each harmonic dynamically and uses adaptive tracking mechanisms that adjust to subject movement and changing distances, allowing accurate heart rate estimation even when the subject is not static or is beyond 80 cm from the radar.
Solution Approach 2:
The patent employs parameter changes through adaptive processing of multiple harmonics using individual NLS estimations. This approach allows the system to maintain measurement precision under varying conditions (distance, movement) by adjusting the estimation parameters for each harmonic based on the actual signal characteristics, thereby improving adaptability to dynamic scenarios.
4Measurement precision
If individual search regions are used for each harmonic frequency estimate, then frequency estimation accuracy improves, but computational complexity increases
Solution Approach 1:
The patent segments the frequency estimation process by creating individual search regions for each harmonic (2nd, 3rd, 4th harmonics). This segmentation allows parallel independent processing of each harmonic, improving frequency estimation accuracy while managing computational complexity through modular organization of the estimation tasks.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides reliable and efficient heart rate estimation by minimizing interference and improving signal-to-noise ratio, enabling accurate monitoring without requiring direct contact and maintaining privacy.
Implementation Method 1
a transmitter for irradiating at least one body region of a person with radar radiation
Implementation Method 2
a receiver for generating a receiver signal from reflected radiation from the at least one body region
Data Source
Figure 1~2
Figure 3
Figure 4~5
AI summary
The invention relates to a method for vital sign monitoring using a radar sensor system (1), the radar sensor system (1) comprising a transmitter (2), a receiver (3) and processing device (5), wherein: the transmitter (2) irradiates (100) at least one body region (21) of a person (20) with radar radiation (30); the receiver (3) generates (110) a receiver signal from reflected radiation (11) from the at least one body region; the processing device (5) generates, for each of a plurality of processing windows, a displacement signal based on the receiver signal, which displacement signal characterizes a body motion comprising as oscillating motions a breathing motion and a heartbeat motion, and calculating an estimated fundamental frequency for at least one oscillating motion. In order provide reliable and efficient means for life sign monitoring, the invention provides that the processing device (5), based on the displacement signal, applies an adaptive Nonlinear Least Squares method to calculate (250) a plurality of frequency estimates (fr1, fr2, fr3), each of which corresponds to one of a plurality of harmonics of a first oscillating motion, wherein the processing device (5) uses an individual search region (Ah1, Ah2, Ah3) for each frequency estimate (fr1, fr2, fr3), adapts at least one search region (Ah1, Ah2, Ah3) for at least one processing window, and calculates (300) a first estimated fundamental frequency (fh) for the first oscillating motion based on the frequency estimates (fr1, fr2, fr3).