报告标题：Tuning into my heart through wearables: towards a formal cardiac digital twin
报告时间：1月4日13：00
报告地点：理科大楼B211
报告摘要：
Digital Twins (DTs) mimic a physical system using a digital version of the real system. While these have been explored in many domains, digital twins of human organs are yet to be created, especially those that are inspired by formal methods. To this end, we propose the first Cardiac Digital Twins (CDTs) by leveraging two key innovations from our research group.
The first is a real-time model of the heart, that is based on a network of hybrid automata to represent the cardiac conduction system that mimics the rhythmic electrical activity of a normal heart. The model can be parametrised to exhibit disease states in real-time, and this approach is being used by MathWorks for closed loop validation of pacemakers in real-time. This work has raised the interest of both device manufacturers and certification agencies, especially in the USA. Our group has expertise in digital biomarkers obtained from wearables, such as Electrocardiograms (ECGs) and Photoplethysmograms (PPGs). These provide a window into the cardiac cycle and we have already shown that the two signals are strongly correlated. Hence, a second innovation is related to using wearables to personalise the real-time heart model, so that the model generates ECGs matching that of an individual in different states. Our approach paves the way for developing personalised therapies, real time monitoring, and accurate estimation of heart rate variability.
报告人简介：
Partha is the Professor and Head of the Department of Electrical and Computer and Software Engineering at the University of Auckland.
Partha's research interests are in safety of AI, ethical AI, and AI applications in cyber-physical systems in digital health, autonomous systems and Machine Learning for Real-Time Systems. His work has both academic and industrial uptake, including recent work on Logical Synchrony Networks with Google https://deepmind.google/
Earlier, he co-founded APIMatic: apimatic.io, a cloud services company with two of his PhD students, which is a global leader on automatic SDK generation from APIs. His work on digital twins of human organs, such as the heart and the gut has influenced the work of major partners on this topic such as Mathworks: https://www.mathworks.com/