Bioimpedance Spectrography System Correcting Breathing Artefacts
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Solution Overview
Problem
Current bioimpedance systems face accuracy issues due to breathing distortions, which require long measurement times and subject stillness to average over multiple cycles, affecting the precision of fluid buildup assessment in heart failure patients.
Innovation Solution
A bioimpedance spectrography system that captures breathing signals to adjust tissue characterization functions, correcting for breathing artefacts by synchronizing impedance measurements with the respiratory cycle, allowing for more accurate parameter estimation with fewer measurement points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple frequency measurements are performed to improve tissue characterization accuracy, then measurement precision is improved, but measurement time increases due to the need to average over multiple breathing cycles
Solution Approach 1:
The system performs preliminary action by capturing the breathing pattern signal before processing impedance measurements, and uses this information to pre-select or pre-weight measurements taken at optimal respiratory phases (such as end-expiration), thereby avoiding the need to collect and average data across multiple complete breathing cycles
Solution Approach 2:
The system dynamically adjusts the tissue characterization process by varying the weighting or selection of impedance measurements based on the real-time breathing phase. Measurements are dynamically weighted according to their reliability at different respiratory phases, with greater emphasis placed on measurements taken at end-expiration when tissue geometry is most stable
2Reliability
If measurements are averaged over multiple sweeps to compensate for breathing artefacts, then measurement reliability is improved, but device complexity and operational requirements increase due to the need for subject stillness
Solution Approach 1:
The breathing pattern is captured and analyzed in advance to identify optimal measurement phases before the actual tissue characterization measurements are finalized. This preliminary analysis allows the system to select or weight measurements appropriately, eliminating the need for subjects to maintain stillness throughout multiple measurement cycles
Solution Approach 2:
The system converts the harmful effect of breathing-induced tissue movement into a beneficial selection criterion. By detecting the breathing phase, the system identifies and utilizes measurements taken at end-expiration when tissue geometry is naturally most stable and reproducible, transforming respiratory motion from a source of error into a guide for optimal measurement timing
3Productivity
If fewer measurement points are used to reduce measurement time, then productivity is improved, but measurement precision deteriorates due to insufficient data for accurate parameter estimation
Solution Approach 1:
The system applies local quality by focusing measurement resources on specific, high-value data points taken at optimal respiratory phases (particularly end-expiration). Rather than uniformly distributing measurements across all phases, the system concentrates analytical weight on measurements taken when tissue geometry is most stable, achieving high precision with fewer total measurement points
Solution Approach 2:
The system changes the parameter of measurement selection based on breathing phase detection. By dynamically adjusting which measurements are used or weighted based on respiratory phase parameters, the system maximizes information content from fewer measurements, achieving accurate parameter estimation without requiring large numbers of measurement points
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 tissue parameter derivation in a shorter time, reducing measurement cycles and improving diagnostic efficiency for fluid buildup assessment in heart failure patients.
Implementation Method 1
a current source for applying an ac current to the body tissue; a reading arrangement for reading a voltage from the body tissue; a processor for deriving a frequency-dependent impedance function from the applied current values and the read voltages
Implementation Method 2
a breathing monitor for monitoring or deriving a breathing pattern of the user... In fact, recording impedance to measure some of these signals is well-known in the fields of impedance cardiography and impedance pneumography
Data Source
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AI summary
A device and method for bioimpedance spectrography is corrected for breathing artefacts.A breathing signal is used in conjunction with the impedance signal to adjust for the time within the respiratory cycle at which the measurements are made. The correction allows the device to characterize tissue parameters accurately with fewer measurement points.