Radar Breathing Monitor Using Autocorrelation Phase Lag
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for monitoring breathing motion, particularly in infants and patients with neuromuscular diseases, face challenges with high uncertainties and errors in measuring the phase lag between chest and abdominal motions, necessitating a more precise and non-invasive technique.
Innovation Solution
A radar sensor system using a radar transmitting unit and receiving unit, along with an evaluation and control unit, calculates the autocorrelation function and Fourier transform of reflected radar signals to determine breathing-characteristic parameters such as phase lag and amplitudes, allowing for precise measurement of breathing motion without contact and reducing noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If plethysmography methods are used to monitor breathing motion, then breathing parameters can be measured, but large uncertainties and errors in phase lag measurement occur
Solution Approach 1:
The patent replaces mechanical plethysmography sensors with a radar-based measurement system. The radar system uses electromagnetic waves to detect chest and abdominal motion, eliminating the need for physical contact sensors that cause measurement uncertainties. The radar transmitter sends continuous wave signals that reflect off the subject's body, and the receiver captures these reflected signals to determine breathing parameters including phase lag with high precision.
Solution Approach 2:
The patent introduces radar waves as an intermediary medium to measure breathing motion. Instead of directly measuring mechanical displacement with contact sensors, the system uses electromagnetic wave reflection to indirectly detect chest and abdominal motion. This intermediary approach allows for contactless measurement, improving both precision and reliability of phase lag determination.
2Reliability
If contactless radar Doppler measurements are used, then measurement reliability improves, but measurement precision of phase lag remains insufficient
Solution Approach 1:
The patent employs parameter changes in the radar signal processing to improve phase lag measurement precision. The system varies the radar carrier frequency and processes signals at different frequencies to extract breathing parameters. By analyzing the phase difference of reflected signals at multiple frequencies and applying autocorrelation functions, the system achieves precise phase lag measurement while maintaining contactless operation.
Solution Approach 2:
The patent uses excessive action by implementing a comprehensive signal processing framework that goes beyond basic Doppler measurement. The system calculates autocorrelation functions, performs Fourier transforms, and analyzes multiple signal parameters simultaneously. This excessive processing approach ensures accurate extraction of phase lag information from the radar signals, overcoming the precision limitations of simple Doppler methods.
3Measurement precision
If signal processing with autocorrelation function is applied, then measurement precision improves, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-processing the radar signals through autocorrelation calculation before further analysis. The autocorrelation function is computed on the received radar signals to enhance the breathing signal components and suppress noise. This preliminary processing step prepares the signals for subsequent Fourier transform and phase lag calculation, improving measurement precision while organizing the computational workflow.
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 method provides accurate, non-invasive monitoring of breathing motion with reduced errors, enabling effective diagnostics for patients with neuromuscular diseases and identifying pulmonary or diaphragmatic breathing patterns.
Implementation Method 1
a radar transmitting unit (12) having one radar transmitting antenna and being configured for transmitting radar waves (14) towards the subject (24), a radar receiving unit (16) having one radar receiving antenna and being configured for receiving radar waves (18) that have been transmitted by the radar transmitter unit (12) and have been reflected by the subject (24)
Implementation Method 2
receiving radar waves (18) that have been transmitted by the radar transmitter unit (12) and have been reflected by the subject (24)
Implementation Method 3
calculate the autocorrelation function and the Fourier transform of the received radar signals
Implementation Method 4
calculate the autocorrelation function and the Fourier transform of the received radar signals
Implementation Method 5
an evaluation and control unit that is at least configured for evaluating Doppler information from the radar waves received by the radar receiving unit
Data Source
Figure 1
Figure 2a~2b
Figure 3~4
AI summary
A method of operating a radar sensor system (10) for monitoring a breathing motion of a subject (24). The radar sensor system (10) includes one radar transmitting antenna (12) and one radar receiving antenna (16) and an evaluation and control unit (22) for evaluating Doppler information from the received radar waves (18). The method comprises transmitting radar waves (14) towards a chest (26) and an abdominal region (28) of the subject (24), receiving radar waves (18) reflected by the subject (24), calculating (38) the autocorrelation function of the received radar signals, calculating (40) the Fourier transform A(y) of the calculated autocorrelation function, determining and recording (42) values of at least two peaks of the calculated Fourier transform A(y), and, from the recorded determined values of the at least two peaks, determine (46, 48) at least one breathing-characteristic parameter of the breathing motion of the subject (24).