ECG Analyzer Automates LAVA Detection via QRS-Guided Time Ranges
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional techniques for analyzing intracardiac electrocardiograms to identify abnormal sites in the ventricle for ventricular tachycardia treatment are cumbersome and time-consuming due to the need for manual adjustment of analysis time ranges and the presence of noise, making it difficult to accurately detect Local Abnormal Ventricular Activities (LAVA).
Innovation Solution
An electrocardiogram analyzer that synchronizes body surface and intracardiac electrocardiogram acquisition, using the QRS waveform to automatically set an analysis time range for frequency analysis, thereby calculating an index value for LAVA ratio, reducing manual intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adjustment of analysis time range is performed for frequency analysis of intracardiac electrocardiogram, then measurement precision of LAVA detection is improved, but loss of time increases due to lengthy manual setting process
Solution Approach 1:
The system performs preliminary action by automatically setting the analysis time range based on the QRS waveform detection from body surface electrocardiogram before the actual frequency analysis is performed. The range setting section pre-determines the optimal time window (e.g., -0.2 to 0.2 seconds relative to QRS) so that when frequency analysis is needed, the analysis time range is already prepared and can be immediately applied to the intracardiac electrocardiogram without manual intervention.
Solution Approach 2:
The body surface electrocardiogram serves as an intermediary to determine the analysis time range for the intracardiac electrocardiogram. Instead of directly analyzing the noisy intracardiac signal to set the time range, the system uses the cleaner body surface ECG QRS waveform as a reference marker to automatically define the optimal analysis window, thereby avoiding time-consuming manual adjustment while maintaining detection accuracy.
2Difficulty of detecting and measuring
If frequency analysis is performed on intracardiac electrocardiogram with noises and overlapping waveforms, then LAVA detection capability is improved, but device complexity increases due to need for manual parameter adjustment
Solution Approach 1:
The system implements self-service by automatically determining the analysis time range without requiring manual intervention. The range setting section autonomously processes the body surface electrocardiogram, detects QRS waveforms, and calculates the appropriate time window for frequency analysis of the intracardiac electrocardiogram, thereby eliminating the need for operators to manually adjust parameters while maintaining effective LAVA detection.
Solution Approach 2:
The system changes the parameter of analysis time range from a manually adjustable variable to an automatically calculated value based on QRS waveform detection. By transforming the time range setting from a subjective manual process to an objective automated calculation using body surface ECG data, the system reduces device complexity while preserving the ability to detect LAVA in noisy intracardiac signals.
3Measurement precision
If multiple mapping points are analyzed to identify abnormal sites, then measurement precision of abnormal site identification is improved, but loss of time increases due to cumulative manual setting required for each point
Solution Approach 1:
The system performs preliminary action by establishing a universal time range setting method based on body surface ECG QRS waveforms that can be applied to all mapping points. This pre-established automated range determination allows the same efficient analysis protocol to be consistently applied across hundreds of mapping points without requiring manual re-adjustment for each location, thereby maintaining high identification accuracy while significantly reducing total analysis time.
Data Source
Figure 1
Figure 2A~2B
Figure 3A~3B
AI summary
An electrocardiogram analyzer includes a first acquiring section that acquires a body surface electrocardiogram of a subject, a second acquiring section that acquires an intracardiac electrocardiogram of a ventricle of a heart of the subject, and an analyzing section that performs a frequency analysis on the intracardiac electrocardiogram and includes a range setting section that sets an analysis time range of the frequency analysis in the intracardiac electrocardiogram based on a unit waveform of the body surface electrocardiogram, and a calculating section that, in the analysis time range, performs the frequency analysis on the intracardiac electrocardiogram, and that calculates an index value indicating a ratio of local abnormal ventricular activities in the intracardiac electrocardiogram.