Micropower Impulse Radar Signal Processing for Cardiopulmonary Data
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Solution Overview
Problem
Current medical imaging technologies face challenges in providing non-invasive, accurate, and efficient quantitative measurements of physiological functions such as heart and lung functions, particularly in distinguishing motion artifacts from static reflections, which affects the reliability of cardiopulmonary data.
Innovation Solution
The integration of micropower impulse radar (MIR) with ultra-wide band (UWB) radar and advanced signal processing techniques, including range delay circuits, balanced receivers, and sophisticated signal processing algorithms, to enhance the detection of cardiopulmonary data by suppressing static reflections and amplifying motion artifacts, thereby improving signal-to-noise ratio and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional radar or imaging technologies are used, then structural imaging can be achieved, but accurate quantitative measurements of physiological functions cannot be obtained
Solution Approach 1:
The signal processing is segmented into distinct stages: static reflection suppression, motion artifact extraction, and physiological parameter calculation. This segmentation allows each processing stage to optimize for its specific function, improving overall measurement precision while maintaining reliability.
Solution Approach 2:
Motion artifacts serve as an intermediary phenomenon that indirectly reveals physiological information. By detecting and analyzing these motion artifacts caused by cardiopulmonary movements, the system obtains quantitative physiological measurements without direct contact or invasive procedures.
2Measurement precision
If signal processing focuses on static reflections, then structural information is obtained, but motion artifacts containing physiological data are suppressed
Solution Approach 1:
The system extracts motion artifact signals from the total radar return by subtracting the dominant static reflection components. This extraction process isolates the physiologically relevant motion information while discarding irrelevant static background signals.
Solution Approach 2:
The signal processing dynamically adapts to separate static and motion components. By continuously analyzing signal characteristics and applying adaptive filtering, the system maintains optimal separation between static reflections and motion artifacts throughout measurement.
3Measurement precision
If conventional imaging methods are used, then visual representation is achieved, but quantitative physiological measurements are not available
Solution Approach 1:
The system replaces complex mechanical or optical imaging systems with electromagnetic radar sensing combined with signal processing. This substitution achieves quantitative physiological measurements through non-contact electromagnetic field interaction, simplifying the physical apparatus while maintaining measurement capability.
Solution Approach 2:
The system changes the measurement parameter from visual/image-based detection to electromagnetic reflection-based detection. By measuring changes in radar signal characteristics (amplitude, phase, time-of-flight) caused by physiological movements, the system obtains quantitative data without complex imaging hardware.
4Reliability
If the radar system detects all reflections, then complete signal information is obtained, but signal-to-noise ratio is reduced due to dominant static reflections
Solution Approach 1:
The system converts the harmful effect of dominant static reflections into a benefit by using them as a reference signal. By characterizing and subtracting the static reflection pattern, the system enhances the visibility of weaker motion artifact signals, effectively improving signal-to-noise ratio.
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
This approach enables precise and reliable quantitative measurements of cardiopulmonary functions by effectively distinguishing and amplifying motion artifacts, leading to improved diagnostic capabilities and enhanced medical imaging technology.
Implementation Method 1
a new type of medical imaging technology based on a variant of ultra-wide band (UWB) radar known as micropower impulse radar (MIR)
Implementation Method 2
The transmitter generates a series of low-voltage, short-duration pulses... reflections are received from the environment and fed to the receiver
Data Source
AI summary
Disclosed is a variant of ultra-wide band (UWB) radar known as micropower impulse radar (MIR) combined with advanced signal processing techniques to provide a new type of medical imaging technology including frequency spectrum analysis and modern statistical filtering techniques to search for, acquire, track, or interrogate physiological data. Range gate settings are controlled to depths of interest within a patient and those settings are dynamically adjusted to optimize the physiological signals desired.