Cardiac Mapping Using Wavelet-Domain QRS Duration Analysis
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Solution Overview
Problem
Current methods for evaluating the atrial substrate in atrial fibrillation patients during sinus rhythm are limited in identifying diseased cardiac tissue, as they primarily rely on peak-to-peak voltage of intracardiac electrograms without effectively utilizing QRS activity duration.
Innovation Solution
A method involving the transformation of electrogram signals into the wavelet domain using continuous wavelet transformation, computing an energy function, and determining QRS activity duration, which is then used to create a graphical representation on a three-dimensional cardiac model to identify areas of diseased substrate by exceeding a preset threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If peak-to-peak voltage of intracardiac electrograms is used to evaluate atrial substrate, then the evaluation method is simple, but the ability to identify diseased cardiac tissue is limited
Solution Approach 1:
The patent transforms the electrogram signal from the time domain to the wavelet domain, changing the parameter space from simple peak-to-peak voltage to a two-dimensional scalogram G(f,t) that captures both frequency and time information. This parameter transformation enables more comprehensive characterization of QRS activity duration while maintaining computational feasibility through wavelet transformation.
Solution Approach 2:
The invention introduces a new dimension by computing QRS activity duration in the wavelet domain rather than relying solely on time-domain peak-to-peak voltage. This adds temporal duration information as a separate evaluative dimension, creating a more robust assessment framework that combines voltage magnitude with activity duration to improve diseased tissue identification.
2Measurement precision
If QRS activity duration is computed using wavelet transformation and energy function, then the identification of diseased substrate is enhanced, but the computational complexity increases
Solution Approach 1:
The patent introduces the wavelet scalogram G(f,t) as an intermediary representation between the raw electrogram signal and the final QRS duration measurement. This intermediary transforms the complex signal analysis problem into a more manageable form by providing a time-frequency representation that simplifies the subsequent energy function computation and duration detection processes.
Solution Approach 2:
The invention replaces traditional time-domain signal processing methods with wavelet transformation, substituting mechanical/time-based analysis with a frequency-time domain approach. This substitution enables more precise detection of QRS activity boundaries through energy function analysis in the wavelet domain, improving measurement precision while managing computational complexity through efficient wavelet algorithms.
Data Source
AI summary
QRS activity duration may be indicative of cardiac tissue health. Accordingly, maps of QRS activity duration may be beneficial to practitioners. To this end, an electroanatomical mapping system can receive an electrogram signal and analyze it by transforming it into the wavelet domain, computing an energy function of the resultant scalogram, and computing QRS activity duration using the energy function. A graphical representation of the QRS activity duration can be output, for example on a three-dimensional cardiac model. Areas of diseased substrate can be identified on the output; in some aspects of the disclosure, diseased substrate corresponds to areas where the QRS activity duration exceeds a preset threshold, such as about 70 ms.