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• W412317186 abstract "The electrocardiograph (ECG) is a common clinical and biomedical research tool used for both diagnostic and prognostic purposes. In recent years computer aided analysis of the ECG has enabled cardiographic patterns to be found which were hitherto not apparent. Many of these analyses rely upon the segmentation of the ECG into separate time delimited waveforms. The instants delimiting these segments are called the “fiducial points”. Rapid automatic identification of the fiducial points is a task which the biomedical engineer needs to perform as a prerequisite to further analysis. To the researcher, post-processing of pre-recorded results is an acceptable mode of analysis. However clinical staff require an immediate real-time diagnosis. This thesis is concerned with the detection of fiducial points using methods which lend themselves to real-time analysis, suitable for use in the development of systems intended for environments where immediate results are called for. By way of introduction, an examination of contemporary methods of fiducial point detection is presented, followed by a discussion of the conventional methods of assessing their performance. It is found that these assessment methods, whilst widely used, are not only mathematically imprecise but are formed in such a way as to be useful to the biomedical engineer, but not to the clinician. An alternative assessment measure which overcomes these problems is proposed, and examples presented to demonstrate how the proposed new measure can be used. Secondly, a novel method of ECG peak detection is presented. Since real-time" @default.
• W412317186 created "2016-06-24" @default.
• W412317186 creator A5076835181 @default.
• W412317186 date "2009-01-01" @default.
• W412317186 modified "2023-09-25" @default.
• W412317186 title "Real time extraction of ECG fiducial points using shape based detection" @default.
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