Cell-to-sensor distance estimation for epicardiac measurements

Atrial fibrillation (AF) is a cardiac arrhythmia characterized by rapid and irregular atrial beating and is correlated with stroke and sudden death. Yet, the mechanisms underlying atrial fibrillation remain still unresolved and challenging to model. To get better understanding of the principles underlying AF, measurements have been carried out with a high resolution electrode array positioned directly on the heart during open heart surgery, called an electrogram. Based on these electrogram measurements it is possible to develop models that can be used to better understand the principles underlying AF and estimate important tissue properties (e.g., conductivity) that play an important role in causing AF. An important parameter in these models is the distance from each sensor of the array to the atrial tissue. As the heart is not a regular and flat surface, this distance will vary in practice.

Assignment

In this assignment we would like to develop an algorithm that can estimate the sensor-to-cell (tissue) distance based on measured electrograms. One way to approach this problem is to investigate the relation between sensor-to-cell distance, and the amount of damping that the signals experience on the sensor compared to a standardised potential.

Requirements

Signal processing background: estimation & detection. Will benefit from theoretical background in EM.

Contact

dr.ir. Richard Hendriks

Signal Processing Systems Group

Department of Microelectronics

Last modified: 2019-12-23