2 research outputs found
Towards a better understanding of the precordial leads : an engineering point of view
This thesis provides comprehensive literature review of the electrocardiography evolution to highlight the important theories behind the development of the electrocardiography device. More importantly, it discusses different electrode placement on the chest, and their clinical advantages. This work presents a technical detail of a new ECG device which was developed at MARCS institute and can record the Wilson Central Terminal (WCT) components in addition to the standard 12-lead ECG. This ECG device was used to record from 147 patients at Campbelltown hospital over three years. The first two years of recording contain 92 patients which was published in the Physionet platform under the name of Wilson Central Terminal ECG database (WCTECGdb). This novel dataset was used to demonstrate the WCT signal characterisation and investigate how WCT impacts the precordial leads. Furthermore, the clinical influence of the WCT on precordial leads in patients diagnosed with non-ST segment elevation myocardial infarction (NSTEMI) is discussed. The work presented in this research is intended to revisit some of the ECG theories and investigate the validity of them using the recorded data. Furthermore, the influence of the left leg potential on recording the precordial leads is presented, which lead to investigate whether the WCT and augmented vector foot (aVF) are proportional. Finally, a machine learning approach is proposed to minimise the Wilson Central Terminal
Evaluating a hierarchical approach for heartbeat classification from ECG.
Several types of arrhythmias that can be rare and harmless, but
may result in serious cardiac issues, and several ECG analysis methods
have been proposed in the literature to automatically classify the various
classes of arrhythmias. Following the Association for the Advancement of
Medical Instrumentation (AAMI) standard, 15 classes of heartbeats can be
hierarchically grouped into five superclasses. In this work, we propose to
employ the hierarchical classification paradigm to five ECG analysis methods
in the literature, and compare their performance with flat classification
paradigm. In our experiments, we use the MIT-BIH Arrhythmia Database and
analyse the use of the hierarchical classification following AAMI standard and
a well-known and established evaluation protocol using five superclasses. The
experimental results showed that the hierarchical classification provided the
highest gross accuracy for most of the methods used in this work and provided
an improvement in classification performance of N and SVEB superclasses