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BNG Presentation by Dr. Premananda Indic |
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| Category: | College Of Engineering | |
| Date & Time: |
Thursday , 10/11/2012 from 12:30 PM to 01:30 PM |
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| Location: | Txt - 102 | |
| Admission: | Free! | |
| Sponsored by: | BNG Faculty Search Committee | |
| Contact: |
Dr. Yong Kim ykim@umassd.edu 508-999-8452 |
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| Description: | TOPIC: Understanding dynamic markers of physiological disorders using engineering approaches ABSTRACT: In this talk, I will discuss how engineering principles from nonlinear dynamics can be applied to understand the abnormal behavior of physiological rhythms during certain pathological conditions, as well as new methods that can be developed for quantifying and restoring rhythmicity. I will demonstrate that physiological signals contain dynamic markers of vulnerability. By employing nonlinear signal processing tools, we are able to extract this hidden information. In addition I will show that biological tissues composed of a population of coupled cellular oscillators that are responsible for generating these physiological rhythms, exhibit a variety of complex behaviors. Based on the theory of coupled oscillators, we derive conditions for different states of a network and apply this theoretical formulation to understand the dynamics of cellular oscillators. Our analysis reveals several salient features of physiological disorders such as suicidal thinking in major depression, apnea in preterm infants and seizures in epileptic patients. I will also discuss our effort in building a therapeutic intervention device for the reduction of apnea episodes in preterm infants admitted to neonatal intensive care units. Biography: Premananda Indic is a research faculty in the Department of Neurology, University of Massachusetts Medical School. He obtained his PhD in the area of nonlinear dynamics and nonlinear signal processing from Cochin University of Science and Technology, India and completed postdoctoral training in biomathematical modeling from Harvard University. Dr. Indic’s research is devoted to understanding the dynamics of physiological systems by employing methods in nonlinear dynamics and nonlinear signal processing. The major goals of his research is to develop signal processing algorithms to detect as well as anticipate the abnormal behaviors of the physiological signals and develop appropriate countermeasures to control the dynamics of the physiological system. He has been primarily focusing on understanding circadian dysrhythmias, apnea and epilepsy from the corresponding physiological signals. | |
