Parametric heart modelling and in silico closed-loop validation of implantable devices
type: CreativeWork
description: Medical Cyber-Physical systems (MCPS), such as cardiac pacemakers and implantable cardioverter defibrillators (ICDs), are life-critical and context-aware. These devices have been increasingly used to provide continuous health-care for patients. The complicated heterogeneous physical dynamics of patients brings distinct challenges for the device development and validation. Testing implantable devices in a closed-physiologic-loop with the actual organ can provide key insights into design safety and treatment efficacy, but this is rarely practical or comprehensive. An in silico closed-loop validation platform allowing interactive and clinically relevant evaluation is desirable. The in silico closed-loop system, incorporating a physiological environment model, is likely to reveal safety risks at the early stage of development before animal testing and clinical trials. However, the closed-loop validation of implantable cardiac device is yet to be thoroughly investigated. Hence, this research proposes three key methodologies to address this need: heart modelling, electrogram (EGM) modelling and automation of closed-loop validation. In an ideal closed-loop system, a heart model responds to the device outputs in realtime according to the underlying physiological dynamics. Although biophysically detailed models provide accurate and realistic insights with predictive dynamics, they are unable to respond in real-time due to the expensive computational cost. While existing simplified models can provide real-time responses, they may not have the necessary dynamic features. We address this problem with a new high-level (abstracted) physiologically based computational heart model. The model comprises a network of nodes along the cardiac conduction system. Each node represents distinct regional electrical action potential behaviour. These nodes are connected by path models which encode the biophysics of tissue conduction. The regional electrophysiology and paths are modelled with h…
abstract: Medical Cyber-Physical systems (MCPS), such as cardiac pacemakers and implantable cardioverter defibrillators (ICDs), are life-critical and context-aware. These devices have been increasingly used to provide continuous health-care for patients. The complicated heterogeneous physical dynamics of patients brings distinct challenges for the device development and validation. Testing implantable devices in a closed-physiologic-loop with the actual organ can provide key insights into design safety and treatment efficacy, but this is rarely practical or comprehensive. An in silico closed-loop validation platform allowing interactive and clinically relevant evaluation is desirable. The in silico closed-loop system, incorporating a physiological environment model, is likely to reveal safety risks at the early stage of development before animal testing and clinical trials. However, the closed-loop validation of implantable cardiac device is yet to be thoroughly investigated. Hence, this research proposes three key methodologies to address this need: heart modelling, electrogram (EGM) modelling and automation of closed-loop validation. In an ideal closed-loop system, a heart model responds to the device outputs in realtime according to the underlying physiological dynamics. Although biophysically detailed models provide accurate and realistic insights with predictive dynamics, they are unable to respond in real-time due to the expensive computational cost. While existing simplified models can provide real-time responses, they may not have the necessary dynamic features. We address this problem with a new high-level (abstracted) physiologically based computational heart model. The model comprises a network of nodes along the cardiac conduction system. Each node represents distinct regional electrical action potential behaviour. These nodes are connected by path models which encode the biophysics of tissue conduction. The regional electrophysiology and paths are modelled with h…
author: Ai, Weiwei
license: https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
date published: 2019
date modified: 2026-07-24T01:03:56Z
provider: University of Auckland
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: ResearchSpace@Auckland

PropertyValue
property ID: Handle
value: https://hdl.handle.net/2292/49258