T-wave alternans detection using adaptable transformation program
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Solution Overview
Problem
Current methods for detecting T-wave alternans in cardiac patients are not sufficiently accurate or flexible, which can lead to missed detections of cardiac arrhythmias and increased instability.
Innovation Solution
An adaptable transformation program is used to apply an alternating sign array to consecutive T-wave signals, with QT intervals sensed and transformed to detect T-wave alternans, incorporating high pass filtering to enhance accuracy and reduce computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods for detecting T-wave alternans are used, then detection capability is provided, but accuracy and flexibility are insufficient leading to missed detections
Solution Approach 1:
The patent implements dynamic adjustment of detection parameters including adaptable transformation programs that modify analysis algorithms based on signal characteristics, and dynamic threshold adjustment that adapts noise thresholds to varying signal conditions. This allows the system to maintain high detection accuracy across different patient conditions while reducing missed detections.
Solution Approach 2:
The system employs multiple transformation parameters (Fast Fourier Transform, Discrete Cosine Transform, Wavelet Transform) that can be selectively applied and adjusted. The noise threshold parameter is dynamically changed based on signal quality assessment, enabling the system to optimize detection accuracy for different signal conditions and patient-specific characteristics.
2Measurement precision
If comprehensive T-wave alternans analysis is performed, then detection capability is improved, but computational resources increase
Solution Approach 1:
The patent implements a multi-stage analysis approach where a preliminary assessment determines the necessary level of analysis. For clear signals, simpler transformation methods are used. For ambiguous cases, more computationally intensive transforms are applied selectively. This partial action approach maintains detection accuracy while minimizing unnecessary computational energy consumption.
Solution Approach 2:
The T-wave analysis is segmented into distinct processing stages: signal acquisition, preliminary filtering, transformation selection, and detailed analysis. Each stage processes only the necessary data with appropriate computational intensity, reducing overall energy consumption while maintaining detection accuracy through focused analysis of critical signal portions.
3Measurement precision
If noise filtering is applied to enhance detection accuracy, then measurement precision improves, but signal processing complexity increases
Solution Approach 1:
The patent replaces complex mechanical signal processing with mathematical transformation methods. Digital signal processing algorithms (Fast Fourier Transform, Wavelet Transform) substitute for analog filtering circuits, reducing hardware complexity while improving noise filtering effectiveness and measurement precision.
Solution Approach 2:
The system dynamically adjusts filtering parameters based on signal characteristics. The transformation type and filtering strength are modified according to the detected signal quality and noise levels, optimizing the balance between noise reduction and signal fidelity without requiring fixed complex processing circuits.
Data Source
AI summary
A method and system for detecting T-wave alternans for use in an implanted medical device uses wave transformation of QT intervals to obtain a reliable measure of TWA. In one embodiment, an array provides alternating sign multiplication factors which are applied respectively to n consecutive QT values. Each successive QT value is high pass filtered and moved sequentially through a queue so that each cycle each of the n QT values is multiplied by one of the factors; the products are summed and made absolute to provide an alternans match value. The alternans match is compared with a noise threshold signal, and alternans is declared when the match exceeds the threshold by a predetermined amount. The array is programmable and can be varied, providing a high degree of flexibility to optimize the test for the patient.