SIAC Seminar - Sensor-based Cardiac System Informatics and Control

Event Details
  • Date/Time:
    • Tuesday December 6, 2011 - Wednesday December 7, 2011
      10:00 am - 10:59 am
  • Location: ISyE Executive Classroom
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Roshan Vengazhiyil


Summary Sentence: Sensor-based Cardiac System Informatics and Control

Full Summary: No summary paragraph submitted.

TITLE: Sensor-based Cardiac System Informatics and Control

SPEAKER; Dr. Hui Yang


 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.

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School of Industrial and Systems Engineering (ISYE)

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  • Created By: Anita Race
  • Workflow Status: Published
  • Created On: Nov 29, 2011 - 9:39am
  • Last Updated: Oct 7, 2016 - 9:56pm