title: Automatic detection of ST-T complex changes on the ECG using filtered RMS difference series: application to ambulatory ischemia monitoring.
abstract: A new detector is presented which finds changes in the repolarization phase (ST-T complex) of the cardiac cycle. It operates by applying a detection algorithm to the filtered root mean square (rms) series of differences between the beat segment (ST segment or ST-T complex) and an average pattern segment. The detector has been validated using the European ST-T database, which contains ST-T complex episodes manually annotated by cardiologists, resulting in sensitivity/positive predictivity of 85/86%, and 85/76%, for ST segment deviations and ST-T complex changes, respectively. The proposed detector has a performance similar to those which have a more complicated structure. The detector has the advantage of finding both ST segment deviations and entire ST-T complex changes thereby providing a wider characterization of the potential ischemic events. A post-processing stage, based on a cross-correlation analysis for the episodes in the rms series, is presented. With this stage subclinical events with repetitive pattern were found in around 20% of the recordings and improved the performance to 90/85%, and 89/76%, for ST segment and ST-T complex changes, respectively.
authors.affiliation: Communications Technologies Group at the Department of Electronic Engineering and Communications, University of Zaragoza, Spain. jogarmo@posta.unizar.es
authors.forename: J
authors.initials: J
authors.lastname: García
authors.forename: L
authors.initials: L
authors.lastname: Sörnmo
authors.forename: S
authors.initials: S
authors.lastname: Olmos
authors.forename: P
authors.initials: P
authors.lastname: Laguna
mesh_terms: D000465:Algorithms; D001698:Biomedical Engineering; D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted; D015716:Electrocardiography, Ambulatory / Q000706:statistics & numerical data*; D006801:Humans; D017202:Myocardial Ischemia / Q000175:diagnosis* / Q000503:physiopathology