Authors:
Laura Burattini
1
;
Wojciech Zareba
2
and
Roberto Burattini
1
Affiliations:
1
Polytechnic University of Marche, Italy
;
2
University of Rochester, United States
Keyword(s):
Signal processing of the digital electrocardiographic signal, Repolarization variability, T-wave alternans.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
Aim of this study was the assessment of a T-wave alternans (TWA) identification procedure based on application of an adaptive match filter (AMF) method, recently developed by ourselves, to a 20-minute digital ECG recording (ECG20). Three-lead ECG20 tracings from 35 patients who survived an acute myocardial infarction (AMI-group) and 35 healthy subjects (H-group) were analysed. The AMI-group showed, on average, increased levels of TWA (P<0.01). Considering that noise may cause false positive TWA detection, a threshold (THRTWA) was defined for TWA magnitude (TWAM) as the mean TWAM +2SD over the H-group. TWAM exceeding this threshold identified a TWA-positive (TWA+) subject as one at increased risk of sudden cardiac death. Fifteen (43%) AMI-patients vs. zero H-subjects were detected as TWA+. This result meets clinical expectation. TWA manifested as a non stationary phenomenon that could even be missed in all TWA+ subjects if our AMF (as well as any other technique) was applied to a sing
le short-term 128-beat ECG series, as usually done in previous reports. In conclusion, our
AMF-based TWA identification technique, applied to 20-minute ECG recordings, yields a good compromise between reliability of time-varying TWA identification and computational efforts.
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