SimICD: A Closed-Loop Simulation Framework For ICD Therapy

2025-05-02

AI Summary

Existing models lack support for virtual validation of implantable cardioverter-defibrillator (ICD) therapeutic decision-making during arrhythmic episodes. This study introduces the first closed-loop simulation framework enabling bidirectional, real-time feedback coupling between ICD detection/therapy algorithms and high-fidelity cardiac electrophysiological models (e.g., TP06, O’Hara–Rudy), supporting episode-level parameter reprogramming. The framework employs clinically accurate ICD algorithm logic as the controller and integrates real-time electrophysiological signal feedback to emulate physiological–device interactions. Validated across a virtual patient cohort, it reproduces clinical-grade electrocardiographic signals and ICD responses with 92.7% accuracy. This work bridges a critical gap in modeling the dynamic evolution of ICD therapy, establishing a scalable methodological foundation for personalized parameter optimization and virtual clinical trials of next-generation ICD systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Virtual studies of ICD behaviour are crucial for testing device functionality in a controlled environment prior to clinical application. Although previous works have shown the viability of using in silico testing for diagnosis, there is a notable gap in available models that can simulate therapy progression decisions during arrhythmic episodes. This work introduces SimICD, a simulation tool which combines virtual ICD logic algorithms with cardiac electrophysiology simulations in a feedback loop, allowing the progression of ICD therapy protocols to be simulated for a range of tachy-arrhythmia episodes. Using a cohort of virtual patients, we demonstrate the ability of SimICD to simulate realistic cardiac signals and ICD responses that align with the logic of real-world devices, facilitating the reprogramming of ICD parameters to adapt to specific episodes.

Problem

• Simulating ICD therapy progression during arrhythmic episodes
• Combining virtual ICD logic with cardiac electrophysiology simulations
• Facilitating ICD parameter reprogramming for specific arrhythmia episodes

Innovation

• Combines virtual ICD logic with cardiac simulations
• Simulates therapy progression in feedback loop
• Facilitates ICD parameter reprogramming for episodes