[Crib-list] SPEAKER: DANILO SCEPANOVIC (MIT) - Computational Research in Boston and Beyond Seminar -- Friday, Dec. 3, 2010 -- Room 32-124 -- Time: 12:30 PM
Shirley Entzminger
daisymae at math.mit.edu
Mon Nov 29 11:31:57 EST 2010
COMPUTATIONAL RESEARCH in BOSTON and BEYOND SEMINAR
DATE: FRIDAY, DECEMBER 3, 2010
TIME: 12:30 PM
LOCATION: Building 32, Room 124 (Stata Center)
Pizza and beverages will be provided at 12:10 PM outside Room 32-124.
TITLE: MODELING AUTONOMIC REGULATION OF SINO-ATRIAL NODE CELL ACTIVITY
SPEAKER: DANILO SCEPANOVIC
(Massachusetts Institute of Technology)
ABSTRACT:
The autonomic nervous system (ANS) regulates bodily functions that are not
under conscious control, such as heart rate, blood pressure, digestion,
etc. The ANS integrates information from the body as a whole and its
activity reflects perturbations caused by various disease processes. We
aim to develop a real-time method to noninvasively estimate the activity
in the two branches of the ANS for use in diagnostics or patient
monitoring.
The current state of the art for cardiac ANS estimation falls under the
topic of heart rate variability (HRV) or cardiovascular system
identification (CSI). HRV and CSI have shown promise for diagnosing and
tracking the progression of diseases such as hypertension, diabetic
neuropathy, heart failure, sleep apnea, and others, as well as quantifying
the consequences of lifestyle changes such as smoking, diet, and exercise.
An opportunity exists to improve the existing methods to increase the
time-resolution and provide more easily interpretable results.
To improve the existing ANS estimation methods, we are incorporating more
physiologic detail into the model of the system, and plan to use this
model to more thoroughly constrain the estimation problem linking heart
beat times to ANS tone. This talk will cover the details of translating
biological data into a mathematical model of the sino-atrial node cell
(the pacemaker of the heart), with a focus on the compromises that must be
made between capturing biological detail and ensuring computational
feasibility and mathematical clarity. The model is realized as a system
of nonlinear ordinary differential equations (ODEs); we also describe a
preliminary implementation using a numerical ODE integrator in serial
(ode15s in Matlab) versus parallel (CVode in Star-P).
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Massachusetts Institute of Technology
Cambridge, MA 02139
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