Ischemia Detection in the Context of a Cardiovascular Status Assessment Tool

Authors

Abstract

Abstract ' In this work a new strategy for automatic ischemic
episodes detection is proposed, considering ST segment
deviation, T wave and QRS morphology characteristics. A new
measure of ST deviation based on time-frequency analysis, and
the use of the expansion in Hermite functions technique for T
wave and QRS complex morphologies, are the key points of the
proposed methodology.
HeartCycle is a European project that aims to improve life
quality of coronary artery disease (CAD) and heart failure (HF)
patients. Within this project, the Medical Risk Assessment
module is responsible for develop models to assess
cardiovascular (CV) risk and status of referred patients. The
present work was performed under the context of CV status
models, where myocardial ischemia plays a central role.
For algorithms validation purposes, the European Society of
Cardiology ST-T database was used. A sensitivity of 99.6% and
a positive predictivity of 90.2% reveal the capacity of the
proposed strategy to perform ischemic episodes identification.

Conference

31th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, September 2009

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