Cardiac Mapping Processor Frequency Analysis
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Solution Overview
Problem
Current medical devices for mapping and ablating cardiac tissue face challenges in accurately processing cardiac electrical activity and identifying sites for therapeutic interventions, particularly in distinguishing between single and multiple dominant frequency values and determining attraction points for effective ablation procedures.
Innovation Solution
A system comprising a catheter shaft with multiple electrodes and a processor that generates time-frequency distributions, applies filters to determine dominant frequency values, and identifies attraction points by correlating signals from multiple electrodes, using techniques such as Fourier transforms and comb filters to differentiate between single and multiple frequency components and visualize sinusoidal representations for diagnostic and therapeutic purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional signal processing methods are used to analyze cardiac electrical activity, then the device complexity is low, but the measurement precision of dominant frequency values and attraction points is insufficient
Solution Approach 1:
The patent segments the cardiac signal analysis into distinct processing stages: initial signal acquisition, time-frequency distribution generation, dominant frequency identification, and attraction point determination. Each stage uses specialized algorithms (e.g., FFT for frequency analysis, zero-crossing detection for timing) to progressively refine the measurement precision without requiring a single overly complex processing step.
Solution Approach 2:
The patent transforms the signal from the time domain to the time-frequency domain using spectrograms and wavelet transforms. This dimensional transformation allows simultaneous analysis of frequency content and temporal characteristics, enabling precise identification of dominant frequency values and their evolution over time, thereby improving measurement precision through domain transformation.
2Measurement precision
If multiple electrodes are used to map cardiac tissue, then the measurement precision and coverage improve, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent merges signals from multiple electrodes by identifying attraction points where dominant frequency values from different electrodes converge or correlate. This consolidation approach allows the system to process multiple electrode inputs efficiently by focusing on shared frequency characteristics rather than treating each electrode independently, thereby improving mapping precision while managing data processing complexity.
Solution Approach 2:
The patent implements a universal signal processing framework that handles data from multiple electrodes through standardized algorithms. The same time-frequency analysis and dominant frequency identification methods are applied across all electrodes, providing consistent measurement precision throughout the cardiac tissue map while simplifying the overall system architecture through methodological uniformity.
3Measurement precision
If advanced filtering and spectral analysis are applied, then the measurement precision of frequency components improves, but the processing time and loss of time increase
Solution Approach 1:
The patent applies preliminary filtering and preprocessing to cardiac signals before full spectral analysis. By pre-identifying potential dominant frequency ranges and applying appropriate band-pass filters beforehand, the system reduces the computational burden of subsequent detailed analysis, thereby improving frequency component differentiation precision while minimizing additional processing time.
Solution Approach 2:
The patent employs periodic signal processing where dominant frequency identification is performed at strategically selected time intervals rather than continuously. This periodic analysis approach maintains measurement precision for detecting frequency changes while significantly reducing the overall processing time and computational resource requirements compared to continuous real-time analysis.
Data Source
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AI summary
Medical devices and methods for making and using medical devices are disclosed. An example system for mapping the electrical activity of the heart includes a catheter shaft. The catheter shaft includes a plurality of electrodes including a first and a second electrode. The system also includes a processor. The processor is capable of collecting a first signal corresponding to a first electrode over a time period and generating a first time-frequency distribution corresponding to the first signal. The first time-frequency distribution includes a first dominant frequency value representation occurring at one or more first base frequencies. The processor is also capable of applying a filter to the first signal or derivatives thereof to determine whether the first dominant frequency value representation includes a single first dominant frequency value at a first base frequency or two or more first dominant frequency values at two or more base frequencies.