Date of Award


Degree Name

Doctor of Philosophy


Electrical Engineering


Joseph H. Pierluissi


A novel and state-of-the-art approach for the analysis of cardiac arrhythmias is proposed. Currently, the analysis of the electrocardiogram is only performed in the time-domain. The proposed method improves the electrocardiogram analysis by adding spatial properties. The spatial properties added to the electrocardiogram allow for the analysis of specific regions inside the human heart where cardiac arrhythmias are suspected to have occurred. In this Dissertation, the concept of electrocardiography was extended using advanced bioelectromagnetism theory. In concrete, the multiple dipole model of the human heart was used to extend the concept of electrocardiography from a temporal analysis to a spatial-temporal analysis. The multiple dipole model of the human heart allows analyzing a specific region of the heart. Therefore, it characterizes the electrical activity of that particular region. The spatial analysis, useful for clinical application, was achieved by using a statistical analysis with a population of normal and abnormal patients. The population of normal patients was used to determine the normal range parameters produced by the multiple dipole analysis. The hypoThesis behind this Dissertation is that abnormal patients lie outside the statistical normal range of the values produced by the multiple dipole analysis. In turn, identifying abnormal patients with this process allows determining the region inside the heart that was found to be abnormal. Four different experiments were performed. The complete cardiac cycle was analyzed, as well as the P-wave, the QRS complex, and the T-wave. A total population of 52 normal patients and 52 abnormal patients was used for the statistical analysis. An efficiency of 80% was found for identifying normal patients. An efficiency of 96%, 36%, 92% and 90% was found for identifying abnormal patients for the complete cardiac cycle, the P-wave, the QRS complex and the T-wave, respectively. It was found that the proposed method is sensitive to the signal-to-noise ratio and cannot provide an accurate analysis of signals that have a low signal-to-noise ratio, such as the P-wave. The proof of concept explored in this Dissertation provided expected results and they indicate that this method could be applied in a clinical trial with a larger population. Therefore, the goals of this Dissertation were achieved.




Received from ProQuest

File Size

94 pages

File Format


Rights Holder

Eduardo Morales