Respiration Noise Filtering in Cardiac Localization Systems
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Solution Overview
Problem
Localization signals in medical systems, such as those used for cardiac procedures, are often contaminated with noise from patient respiration, leading to inaccurate positioning of medical devices due to apparent movement of stationary electrodes.
Innovation Solution
A method involving patch electrodes with accelerometers measures acceleration signals to calculate displacement and transform them into the frequency domain, allowing for the identification and filtering of respiration noise using a high-pass filter, ensuring accurate localization data collection at consistent points within the respiration cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional localization systems are used without respiration filtering, then the system structure remains simple, but the positioning accuracy deteriorates due to respiration noise causing apparent electrode movement
Solution Approach 1:
The patent segments the localization signal processing into multiple components: raw localization signal acquisition, separate respiration signal acquisition via accelerometers, frequency domain transformation, spectral analysis to identify respiration frequencies, and selective filtering. This segmentation allows targeted removal of respiration noise while preserving the underlying localization information, thereby improving positioning accuracy without requiring complete system redesign
Solution Approach 2:
The patent introduces accelerometers as intermediary devices attached to the patient's chest to capture respiration movements. These accelerometers serve as mediators that indirectly measure the respiration-induced electrode displacements, allowing the system to identify and filter out respiration noise from the localization signals without directly interfering with the primary localization field or electrodes
2Measurement precision
If respiration filtering is applied to localization signals, then positioning accuracy improves, but signal attenuation occurs reducing the strength of valid localization data
Solution Approach 1:
The patent employs feedback mechanisms where the filtered localization signals are continuously monitored and compared against the original signals. The filtering process uses spectral analysis to identify respiration frequency components, applies selective attenuation only at those frequencies, and preserves the amplitude and phase of non-respiration components. This feedback-based selective filtering ensures that positioning accuracy improves while minimizing loss of valid localization signal energy
3Productivity
If data collection continues throughout the respiration cycle, then productivity is maintained, but data quality deteriorates due to varying electrode positions
Solution Approach 1:
The patent applies periodic action by gating the data collection process to specific phases of the respiration cycle. Using the accelerometer-derived respiration signal, the system identifies consistent reference points (such as end-inspiration or end-expiration phases) and collects localization data only during these periodic windows. This ensures all collected data points correspond to the same anatomical reference position, maintaining data consistency without significantly reducing overall productivity since the gating window captures sufficient data points per cycle
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 effectively filters out respiration noise from localization signals, minimizing signal attenuation and ensuring data collection at consistent points in the respiration cycle, thereby improving the accuracy of medical device positioning within the body.
Implementation Method 1
at least one of the localization system patch electrodes includes an accelerometer capable of measuring acceleration in at least one direction
Implementation Method 2
transforming the displacement signal from the time domain into the frequency domain
Implementation Method 3
applying a high-pass filter to the localization signal of the at least one position measurement sensor to filter out the respiration noise component
Data Source
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Figure 3A~3E
AI summary
A method of filtering respiration noise from a localization signal includes acquiring a localization signal from at least one position measurement sensor within a localization field and acquiring an acceleration signal for at least one localization field generator (e.g., a patch electrode). A displacement signal for the field generator is calculated, for example by integrating the acceleration signal twice, and transformed into the frequency domain in order to calculate a fractional power indicative of patient respiration. The fractional power can then be compared to a threshold value, and the localization signal can be filtered if the fractional power exceeds the threshold value. Alternatively, the acquired acceleration signal can be used to gate collection of data points from the localization signal.