published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat. An implantable cardiac monitor (ICM) is a device used to help physicians diagnose and monitor infrequent cardiac arrhythmias that may not be observed during an ECG recording performed during a normal clinic visit. These devices are implanted under the skin of the chest and simply monitor and record the electrical activity of the heart. The recorded signal is referred to as a subcutaneous electrocardiogram, or SECG. This thesis proposes and tests a novel algorithm that uses an SECG signal to perform PVC detection and is suitable for implementation within an implantable cardiac monitoring device. The proposed algorithm uses a combination of morphological and timing criteria to identify PVCs in near real time. Current commercially-available ICMs do not provide a PVC detection feature, so the proposed algorithm could help provide physicians with valuable additional diagnostic information about a clinically-significant arrhythmia.

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1979. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by Peter A. Bonee, Jr. / B.S.

Cardiac diseases and conduction disorders are associated with stroke, heart failure and sudden cardiac death and are a major health concern worldwide. In the US alone, more than 14 million people suffer from heart rhythm disorders. Current mapping and characterization techniques in the clinic involve invasive procedures, which are time-consuming, costly, and may involve ionizing radiation. In this dissertation, we introduce Electromechanical Wave Imaging (EWI) as a non-invasive, ultrasound-based treatment planning tool for pre-procedure characterization and assessment of arrhythmia in the clinic. In particular, standard EWI processing methods for mapping the electromechanical wave (EW), i.e. the onset of the mechanical activity following the depolarization of the heart, are described and detailed. Next, validation of EWI is performed with 3D electromechanical mapping and the EW propagation is shown to follow the electrical activation in all four chambers of the heart. Demonstration of the value of EWI for the characterization of cardiac arrhythmia is accomplished in vivo in a large animal model. First, EWI is shown capable of localizing the earliest region of activation in the ventricles during pacing from a standard pacemaker lead, as well as during pacing from a novel biological pacemaker. Repeatability is also demonstrated between consecutive cardiac cycle during normal sinus rhythm and during pacing. Then, in the atria, we demonstrate that EWI is capable of accurately identifying focal sources while pacing from several locations in both the left and right atria. In addition to being capable of localizing the focal source, EWI is also shown capable of differentiating between endocardial and epicardial focal sources. Finally, it is shown that EWI can correctly identify regions of infarction and monitor formation of infarcts over several days, after ligation of the left anterior descending coronary artery of canine hearts. Novel processing techniques aimed at extracting quantitative parameters from EWI estimates are then developed and implemented. Details of the implementation of processing methods for estimating the velocity of the EW propagation are presented, and a study of the EW velocity values in a canine heart before and after infarct formation is conducted. Electromechanical cycle length mapping (ECLM), which is aimed at extracting local rates of electromechanical activation in the heart, is then introduced and its implementation detailed. ECLM is subsequently validated in a paced canine heart in vivo. Finally, initial clinical feasibility is demonstrated. First, in the study of treatment of chaotic arrhythmia such as in the case of atrial fibrillation patients undergoing direct current cardioversion, ECLM is shown to be able to confirm acute treatment success. Then, the clinical value of EWI in the electrophysiology lab as a treatment planning tool for the characterization of focal arrhythmia is shown in ventricular tachycardia and Wolff-Parkinson-White patients. EWI is currently only a step away from real-world clinical application. As a non-invasive, ultrasound-based imaging modality, EWI is capable of providing relevant insights into the origins of an arrhythmia and has the potential to position itself in the clinic as a uniquely valuable pre-procedure planning tool for the non-invasive characterization of focal arrhythmias.

published_or_final_version / abstract / Electrical and Electronic Engineering / Master / Master of Philosophy