Model-based Clinical Assist System for Cardiac Ablation

doi:10.1145/3450267.3450539

	Model-based Clinical Assist System for Cardiac Ablation
	Yutong Wu1 ; Renzhi Tang1 ; Eunsuk Kang 2; Zhihao Jiang1
	2021-05
会议录名称	INTERNATIONAL CONFERENCE ON CYBER-PHYSICAL SYSTEMS
页码	110-120
发表状态	已发表
DOI	10.1145/3450267.3450539
摘要	Cardiac Ablation is an effective treatment of arrhythmia in which physicians terminate fast heart rate by transecting abnormal electrical conduction pathways in the heart with RF energy. During the procedure, physicians diagnose the condition of the heart and locate ablation sites by analyzing electrical signals sensed by catheters inserted into the heart. Due to the limited observation of the patient's heart, there may exist multiple heart conditions that can explain historical observations, causing ambiguities in the patient's heart condition. During the procedure, physicians have to visualize and continuously update these suspected heart conditions in their mind, causing heavy mental burden on the physicians. In this paper, cardiac electrophysiology is formalized using a physiological model of the heart, such that the diagnosis problem during cardiac ablation can be formalized as parameter identification and state estimation problems with the heart model. We then propose a model-based clinical assist system which partially solves the diagnosis problem during cardiac ablation. The system enumerates suspected heart conditions by creating "digital twins"of the patient's heart with heart models. The heart models are used to represent and visualize suspected heart conditions, and are systematically updated and removed with new information during the ablation procedure. The system provides more rigorous and intuitive interpretation of current understanding of the patient's heart, and improves the accuracy and efficiency of cardiac ablation procedures by relieving the physicians from demanding low-level reasoning. © 2021 ACM.
会议录编者/会议主办者	ACM SIGBED ; IEEE TCRTS
关键词	Ablation Digital twin Electrophysiology Embedded systems Internet of things Physiological models Ablation procedures Cardiac electrophysiology Diagnosis problem Electrical conduction Electrical signal Estimation problem Historical observation Limited observations
会议名称	12th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2021, part of CPS-IoT Week 2021
会议地点	Virtual, Online, United states
会议日期	May 19, 2021 - May 21, 2021
收录类别	EI
语种	英语
出版者	Association for Computing Machinery, Inc
EI入藏号	20211610225715
EI主题词	Heart
EI分类号	461.1 Biomedical Engineering ; 461.2 Biological Materials and Tissue Engineering ; 641.2 Heat Transfer ; 723 Computer Software, Data Handling and Applications
原始文献类型	Conference article (CA)
引用统计	正在获取...
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/126449
专题	信息科学与技术学院_硕士生信息科学与技术学院_PI研究组_江智浩组
通讯作者	Zhihao Jiang
作者单位	1.ShanghaiTech University 2.Carnegie Mellon University
第一作者单位	上海科技大学
通讯作者单位	上海科技大学
第一作者的第一单位	上海科技大学
推荐引用方式 GB/T 7714	Yutong Wu,Renzhi Tang,Eunsuk Kang,et al. Model-based Clinical Assist System for Cardiac Ablation[C]//ACM SIGBED, IEEE TCRTS:Association for Computing Machinery, Inc,2021:110-120.