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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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TITLE: Sensor-based Cardiac System Informatics and Control
SPEAKER; Dr. Hui Yang
ABSTRACT:
Medical devices in the 21st century are capable of monitoring the cardiac electrical activities in real time and lead to the proliferation of patient monitoring signals. With massive healthcare recordings readily available, there is dire need for the extraction of knowledge pertinent to the cardiac disease process, thereby leading to the early identification and control of cardiac disorders. We intertwined the approaches of physics-based modeling and sensor-based data fusion to promote the study of cardiac system informatics and control. The computational cardiac models not only overcome the practical and ethical limitations in physical experiments but also provide predictive insights on the underlying pathological mechanisms. Here, we modeled the variations of cardiac electrical signaling due to changes in glycosylation of a voltage-gated K+ channel, hERG, responsible for late phase 2 and phase 3 of the human ventricular action potential (AP). The multi-scale cardiac model is developed to integrate the measured changes in hERG channels under different glycosylation treatments, and further predicts the electrical behaviors of cardiac cells and tissues (cable/ring). The experimental results show that reduced glycosylation acts to shorten the repolarization period of cardiac APs, and distort the AP propagation in cardiac tissues. On the other hand, we developed an approach of multiscale recurrence analysis to study the cardiac pathological behaviors in the space-time domain, as opposed to the conventional time delay reconstructed phase space from a single ECG trace. Few, if any, previous approaches studied the relationships between cardiac disorders and multiscale recurrence patterns underlying the cardiac vectorcardiogram (VCG) signals. The integration of wavelets and nonlinear dynamics was experimentally shown to facilitate the prominence of hidden pathological properties that are usually buried in a single scale view. Finally, future research directions in the area will be discussed.
