2017/03/03 by Weiwei Ai, Nitish Patel, Ai, Weiwei +9
Medicine · Neuroscience · #Cardiac electrophysiology and arrhythmias #Cardiac pacing and defibrillation studies #FOS: Biological sciences #FOS: Electrical engineering #FOS: Physical sciences #Medical Physics (physics.med-ph) #Neuroscience and Neural Engineering #Systems and Control (eess.SY) #Tissues and Organs (q-bio.TO) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1703.01107
openalex publication_date 2017/03/03 · openalex created_date 2019/06/27 · openalex updated_date 2026/07/28
Virtual heart models have been proposed to enhance the safety of implantable cardiac devices through closed loop validation. To communicate with a virtual heart, devices have been driven by cardiac signals at specific sites. As a result, only the action potentials of these sites are sensed. However, the real device implanted in the heart will sense a complex combination of near and far-field extracellular potential signals. Therefore many device functions, such as blanking periods and refractory periods, are designed to handle these unexpected signals. To represent these signals, we develop an intracardiac electrogram (IEGM) model as an interface between the virtual heart and the device. The model can capture not only the local excitation but also far-field signals and pacing afterpotentials. Moreover, the sensing controller can specify unipolar or bipolar electrogram (EGM) sensing configurations and introduce various oversensing and undersensing modes. The simulation results show that the model is able to reproduce clinically observed sensing problems, which significantly extends the capabilities of the virtual heart model in the context of device validation.