Paper Info
Title
Myocardial Ischemia Diagnosis Using a Reduced Lead System.
Abstract
This research presents a novel statistical model for diagnosing acute myocardial infarction (AMI). The model is based on features extracted from a reduced lead system consisting of a subset of three leads from the standard 12-lead ECG. We selected a set of relevant parameters commonly used in the clinical practice for ECG-based AMI diagnosis, namely ST elevation and T-wave maximum. We also selectedfeatures, not used in clinical practice, that were derived from vectorcardiography and computed on the reduced three-lead system (pseudo-VCG parameters). To validate the model, we used 104 patients coming from the Physionet STAFF III database which contains 12-lead ECG recordings at baseline and in coronary artery occlusion condition during angioplasty (PTCA). Results show that pseudo-VCG features are able to diagnose AMI slightly better than ST elevation and T-wave maximum features together (area under the ROC curve (AUC) 0.87 vs AUC 0.85). When combining pseudo-VCG features together with ST elevation, and T-wave maximum, the performance improved significantly (AUC 0.95, sensitivity 89.6% and specificity 82.7%). Results indicate a potential for diagnosing AMI using the proposed reduced lead system and the selected set of features. We suggest its possible use for diagnosing AMI in long-term, ambulatory and home monitoring situations, allowing an earlier and faster diagnosis.
Year
DOI
Venue
2018
10.1109/EMBC.2018.8513511
EMBC
Field
DocType
Volume
Myocardial infarction,Computer science,Artificial intelligence,Electrocardiography,Computer vision,ST elevation,Ambulatory,Internal medicine,Cardiology,Clinical Practice,Ischemia,Vectorcardiography,Angioplasty
Conference
2018
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
A. Aranda Hernandez100.34
pietro bonizzi285.81
J. M. H. Karel395.57
Ralf L. M. Peeters46222.61