Wearable Cardiac Defibrillator Personalization Model
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Solution Overview
Problem
Current cardiac defibrillators, both implantable and wearable, face challenges in optimizing defibrillation energy to minimize myocardial damage while ensuring effective termination of ventricular fibrillation, with existing models lacking personalized approaches for varying patient anatomy and electrode configurations.
Innovation Solution
A computational model using imaging scan data and Finite Element Method (FEM) simulations to predict and optimize defibrillation mechanisms in wearable cardiac defibrillators, by modeling myocardial potential gradients and calculating divergence with respect to probabilistic voltage distributions, allowing for personalized electrode configurations that minimize myocardial damage and achieve optimal defibrillation thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If strong shocks are used during defibrillation to ensure effective termination of ventricular fibrillation, then defibrillation efficacy is improved, but myocardial damage and adverse effects increase
Solution Approach 1:
The patent optimizes defibrillation shock parameters (voltage, duration, waveform) to achieve effective defibrillation at lower energy levels. By modifying these parameters and using computational modeling to predict optimal settings, the system maintains high defibrillation efficacy while reducing myocardial damage from excessive shock strength.
Solution Approach 2:
The system performs preliminary computational modeling and simulation to predict the optimal defibrillation threshold for each patient before actual defibrillation. This preliminary action allows customization of shock parameters to the lowest effective level, avoiding the need to use universally strong shocks that cause myocardial damage.
2Manufacturing precision
If personalized computational modeling is implemented to optimize defibrillation for each patient, then defibrillation optimization is improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent creates simplified computational models that replicate the essential electrical properties of the heart without requiring full anatomical reconstruction. These copied models capture the key biophysical characteristics needed for defibrillation threshold prediction, reducing computational complexity while maintaining optimization accuracy.
Solution Approach 2:
The system uses standardized anatomical parameters and simplified tissue conductivity values in the computational models, rather than requiring detailed patient-specific measurements for every parameter. This approach maintains personalized optimization while reducing the complexity of data collection and model construction.
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
The model enables personalized therapy approaches by optimizing defibrillation energy delivery, reducing myocardial damage, and improving defibrillation efficacy, as demonstrated by comparing different electrode configurations and their impact on myocardial voltage gradients and defibrillation thresholds.
Implementation Method 1
Distribution of electric field in the heart is closely related to the nature of defibrillation. Defibrillation shock should be able to depolarize the heart homogeneously
Implementation Method 2
computing, for each of the plurality of biophysical models, a probabilistic distribution of myocardial voltage gradient (C) after defibrillation by combining a first exponential functions rising in amplitude for below a predetermined voltage gradient and a second exponential function decaying in amplitude for above the predetermined voltage gradient
Data Source
Figure 1~2A
Figure 2B
Figure 3
AI summary
This disclosure relates generally to a computational model for personalizing defibrillation mechanism of wearable cardiac defibrillator (WCD). Cardiac defibrillators are lifesaving therapeutic device with potentially harming capacity if not tuned properly. Hence creation of a personalized energy distribution model based on subject's anatomy, rather than a 'one size fits all' approach is preferred. The disclosed model compares the efficiency of standard and nonstandard WCD electrode placement in the torso vest, demonstrating significant differences in defibrillation efficacy associated with different strategies. A new measure is presented for performing such a comparison which combines the DFT and extent of myocardial damage.