The heart is one of our vital organs. It functions by periodically contracting in a rhythmic way. Sometimes, this rhythmic behaviour is affected by abnormalities in the tissue. These conditions are referred to as cardiac arrhythmias. One kind is of specific interest, called atrial fibrillation (AF). To further study AF, methods have been developed to estimate the conductivity of cardiac cells based on the measured electrical signals. In addition, other parameters of interest besides the conductivity are involved. The goal of this project was to consider one of the parameters in the electrogram (EGM) model: the sensor-to-cell height.
First, we studied the effect of the height as a parameter in the model when used for conductivity estimation. To that end, a detector was built with which we can explain the effect of all involved parameters on the ability to accurately estimate any parameters of interest.
In addition, we considered the case where the height is unknown and is estimated, thus possibly including estimation errors. The focus was on the consequences of making errors in the estimation of the height with respect to conduction block detection and conductivity estimation.
Lastly, the effort was made to estimate the height. Here, the optimisation problem of height estimation was formalised and derived as its implementable form. At first, a simplified EGM model was assumed in order to mimic and estimate cell-specific effects, i.e. the cell conductivities. Then, the height was estimated in various situations to study its behaviour and performance under different conditions. Then, also the standard EGM model was used in the same way, after which we also tested the performance of the designed algorithm in combination with existing conductivity estimation methods.

This report is written as part of the Bachelor Graduation Project in the third year of the Electrical Engineering Bachelor programme at the Delft University of Technology. This report is made by a subgroup that is part of a larger project dedicated to finding a solution to frequency feedback in electroacoustic systems, also known as the Larsen effect.

This problem has a long history of literature and many solutions to this problem have been presented. For this project, the focus lies on the application of Adaptive Feedback Cancellation (AFC). This technique uses estimations of the Room Impulse Response (RIR) to minimise the feedback component. This report focuses on estimating such a RIR in the case of a PA system. Several methods will be discussed and compared by implementing and testing them in a simulation environment built in Matlab. The different methods are subjected to a set of performance measurements that provide the necessary information to see for each method and situation if and how the results measure up against a set of predetermined system requirements. From the researched algorithms, one is chosen as the one to be implemented in the final design of the group. At last, some considerations and recommendations are given for implementing one of the algorithms into software and hardware components.