Non-Contact Vital Sign Radar Signal Processing for Exercise
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Solution Overview
Problem
Existing non-contact vital sign detection methods face challenges in accurately measuring vital signs during exercise due to body movement interference.
Innovation Solution
A non-contact exercise vital sign detection method using a processor in a signal processing apparatus, which involves obtaining digital signals, generating phase and vibration frequency maps, selecting candidate positions based on energy thresholds, and inputting target phase data into a machine learning model to predict vital sign parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If non-contact measurement method is used, then subject comfort is improved, but measurement accuracy deteriorates due to body shaking interference during exercise
Solution Approach 1:
The patent segments the measurement signal into multiple frequency components through Fast Fourier Transform (FFT), separating the vital sign frequencies from the body movement interference frequencies. By analyzing specific frequency bands corresponding to heart rate and respiration, the system isolates useful signals from harmful motion artifacts, resolving the contradiction between non-contact measurement and measurement accuracy during exercise.
2Device complexity
If traditional non-contact detection method is used, then device simplicity is maintained, but measurement reliability deteriorates during exercise due to motion interference
Solution Approach 1:
The patent implements dynamic signal processing by continuously updating the frequency spectrum analysis and adaptively selecting frequency components corresponding to vital signs. The system dynamically adjusts to changing exercise intensities and body movements by re-analyzing the frequency spectrum in real-time, maintaining measurement reliability without requiring complex hardware modifications.
Solution Approach 2:
The system employs feedback mechanisms by comparing detected frequency components against expected vital sign ranges and iteratively refining the measurement. The processed frequency information feeds back into the selection and analysis of candidate positions, improving measurement reliability through continuous validation and adjustment based on the detected signal characteristics.
3Speed
If simple energy threshold filtering is used, then processing speed is improved, but measurement precision deteriorates due to false candidate positions
Solution Approach 1:
The patent transitions from one-dimensional energy threshold filtering to two-dimensional frequency-domain analysis by applying FFT to the phase map. This dimensional change enables the system to identify candidate positions based on both energy intensity and frequency characteristics, significantly improving candidate position selection accuracy while maintaining processing efficiency through efficient frequency domain algorithms.
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
Enables accurate non-contact detection of vital sign parameters during exercise by mitigating the interference caused by body movement, thereby improving measurement accuracy.
Implementation Method 1
a transmitting unit, configured to transmit an incident radar signal; a receiving unit, configured to receive a reflected radar signal
Implementation Method 2
obtain a phase map and a vibration frequency map according to the digital signal, where the phase map presents an energy distribution with a distance change relative to an exercise vital sign detection radar and a phase change
Data Source
AI summary
A non-contact exercise vital sign detection method is provided. At least one candidate position having an energy intensity exceeding an energy threshold is pre-selected from a vibration frequency map, and a position having a vibration frequency meeting a vital sign parameter range is then selected as a target position from the at least one candidate position. Accordingly, phase data obtained according to the target position facilitates accurate detection of a vital sign parameter of a subject.