Cardiac Arrhythmia Data Analysis (several projects)

Atrial fibrillation is the most common cardiac arrhythmia which is characterized by an on-going beat-to-beat changing in patterns of electrical activation resulting in complex electrical signals.

Atrial fibrillation is a progressive arrhythmia; initially there are short episodes which terminate spontaneously, but over time these episodes become longer until they do not spontaneously anymore.

Various MSc thesis projects with Erasmus MC are available.

Assignment

Electrical Asynchrony and Cardiac Arrhythmias

Recently, researchers at Erasmus MC discovered that increased electrical asynchrony between the endocardium (inner layer of the cardiac wall) and epicardium (outer layer of the cardiac wall) is associated with persistence of atrial fibrillation.

Circumscriptive areas of endo-epicardial asynchrony may serve as target sites for therapy. However, the exact mechanism underlying endo-epicardial asynchrony is not yet fully understood. Nevertheless, simultaneous high resolution mapping of the endo- and epicardial layer offers the opportunity to examine the relation between signal morphologies (voltages, slope, number of deflections), endo-epicardial electrical asynchrony, wavefront curvatures and transmural angles of electrical waves.

The assignment is to analyze available data sets and propose data models that can explain the patterns of activation.

Ageing and Cardiac Arrhythmias

Atrial fibrillation is associated with ageing. Experimental models have demonstrated that ageing is associated with electrical alterations, including changes in myocyte cell size, electrical uncoupling of muscle bundles and gap junctional remodeling. However, there is no information on the relation between increase in cell size associated with ageing, gap junction remodeling (proteins associated with electrical propagation), electrical uncoupling in relation to signal morphology.

The assignment is to correlate alterations in electrical properties associated with ageing, and to propose data models that can explain this.

Determinants of electrical signal morphology

Accurate analysis of electrical electrograms is of paramount importance prior to ablative therapy of cardiac arrhythmias. The morphology of electrical signals is significantly influenced by the recording technique applied, such as electrode diameter and inter-electrode distances.

The assignment is to analyze the current recording techniques and explain the morphology of the signals as function of the measurement design parameters.

Programmed Electrical Stimulation and Signal Morphology

The progression of atrial fibrillation from an intermittent to a more permanent stage could perhaps be diagnosed from the results of electrical stimulation (pacing). Currently, therapy is not based on the AF stage, and this is likely a major determinant of therapy failure.

The assignment is to unravel AF-related electropathology by utilizing a dedicated, programmed electrical stimulation (‘pacing)’ technique and by quantifying features of paced signals.

Requirements

The assignments are suitable for MSc students in Signals and Systems, and MSc students in Biomedical Engineering that took some signal processing classes.

Matlab is used to analyze the available data.

Contact

dr.ir. Richard Hendriks

Signal Processing Systems Group

Department of Microelectronics

Last modified: 2017-10-20