| Summary: | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. === Cataloged from PDF version of thesis. === Includes bibliographical references (p. 65-68). === Patients who have had an acute coronary syndrome (ACS) are at a relatively high risk of having subsequent adverse cardiac events. Several electrocardiographic (ECG) measures such as heart rate variability, heart rate turbulence, deceleration capacity, T-wave altemans, and morphologic variability have been used to identify patients at an increased risk of recurrent myocardial infarctions and cardiovascular death. In this work, we develop a new ECG-based measure for patient risk stratification called weighted morphologic variability. This measure is based on assessment of beat-to-beat changes in the morphology of consecutive beats. Weighted morphologic variability identifies patients who are at more than four-fold risk for cardiovascular death, which is an improvement in ECG-based risk stratification. The body of this work suggests that prognosticating patients based on electrocardiographic measures is an effective way of identifying those at risk of adverse cardiovascular outcomes. === by Joyatee Mudra Sarker. === M.Eng.
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