Evaluating morphological patterns in atrial epicardial potentials: Clustering of time series potentials during atrial fibrillation

Introduction: Potentials measured at the epicardial surface contain information regarding the conductive properties of the atrial tissue. The current lack of morphological categorization during atrial fibrillation (AF) provokes the usage of unsupervised learning methods to evaluate time series electrograms across the atrial surface. Analysis of...

A heuristic approach to spatial audio using consumer loudspeaker systems

The work presented in this thesis investigates the creation of virtual sound sources in a room equipped with a limited number of loudspeakers. This limited number of loudspeakers is typical for consumer loudspeaker systems. Ideally, these systems can provide a listening experience in which localisation cues are completely present. However, in...

Targetless Camera-LiDAR Calibration for Autonomous Systems

In recent decades, the field of autonomous driving has witnessed rapid development, benefiting from the development of artificial intelligence-related technologies such as machine learning. Autonomous perception in driving is a key challenge, in which multi-sensor fusion is a common feature. Due to the high resolution and rich information, the...

Dual-polarization multi-frequency radar data processing for moving target detection

This project develops and tests algorithms for joint signal processing of data from two radars located on the rooftop of EWI (PARSAX and MESEWI). The particular tasks consist of automatic alignment of radar data in space (2D map) and time by observing moving targets of opportunity in the high-resolution mode. After the data alignment procedure,...

Frequency Domain Joint Estimation of HRF and Stimulus from fUS Data

To better understand how brain signals are processed and even how the human mind works, analyzing the hemodynamic signal model is one of the most essential steps. In the CUBE group of Erasmus MC, functional ultrasound (fUS) data of a mouse’s brain is recorded. By using this fUS dataset, this thesis will solve the problem regarding the joint...

Outlier detection in time series: The Random Projection Outlier Ensemble

Outlier detection in time series has important applications in a wide variety of fields, such as patient health, weather forecasting, and cyber security. Unfortunately, outlier detection in time series data poses many challenges, making it difficult to establish an accurate and efficient detection method. In this thesis, we propose the Random...

Automatic detection of eCAP thresholds: Precision and accuracy of different methods

When a person suffers from severe to profound hearing loss, a cochlear implant (CI) can aid in restoring auditory perception and speech comprehension. To obtain good speech comprehension, fitting of a CI to the user’s specific characteristics is crucial. Fitting can be a time-consuming process which requires the cooperation of a CI user and is...

Rank Detection Based on Generalized Eigenvalue Threshold in Arbitrary Noise

Rank detection is crucial in array processing applications, as many algorithms rely on accurately estimating the rank of the data matrix to ensure optimal performance. Under Gaussian white noise, rank can be detected through eigenvalue analysis. However, in arbitrary noise, prewhitening the data matrix with the noise covariance matrix is...

Distributed Optimisation Using Stochastic PDMM: Convergence, transmission losses and privacy

In recent years, the large increase in connected devices and the data that is collected by these devices has caused a heightened interest in distributed processing. Many practical distributed networks are of heterogeneous nature. Because of this, algorithms operating within these networks need to be simple, robust against network dynamics and...

Exploring the Potential of Performance Bounds in Multi-Source Domain Adaptation

Currently, trained machine learning models are readily available, but their training data might not be (for example due to privacy reasons). This thesis investigates how pre-trained models can be combined for performance on all their source domains, without access to data. This problem is formulated as a Multiple-Source Domain Adaptation (MSA)...

Using Tensor Decompositions To Obtain Biomarkers From Auditory Event-Related Potentials

Brain disorders in children pose significant challenges to their development, impacting cognition, speech, movement, and behavior. The uncertainty surrounding prognostic information at the time of diagnosis leaves families with numerous questions about the future. The Child Brain Lab at Erasmus MC Sophia Children's Hospital conducts IQ,...

Multiway Component Analysis for the Removal of Far Ventricular Signal in Unipolar Epicardial Electrograms of Patients with Atrial Fibrillation

Atrial fibrillation (AF) is one of the more common clinical arrhythmias with a high morbidity and mortality. Despite this, the electrophysiological and pathological mechanisms associated with AF largely remain a mystery, encouraging the use of ever more sophisticated techniques to extract vital information for diagnostic and therapeutic purposes...

Multi-target detection using Relevance Vector Machine

The main purpose of a radar is to detect, recognize, and track objects of interest. When it is known that only a single target is present, the matched filter is proven to be optimal detector. However, in practice, a radar scene often consists of multiple targets. For example, in air surveillance and monitoring applications, multiple aircrafts...

The area of a unipolar electrogram to identify the arrhythmogenic substrate

Background: Unipolar electrograms (U-EGMs) contain additional information about interatrial activation and conduction in their morphology, which may aid towards improved diagnosis and staging of atrial fibrillation (AF).Objective: The primary objective is to investigate regional differences in electrogram area (EA) during SR and AF and to design...

Encoding of Correlated Temporal Information in a Model Cerebellar Loop with Olivary Oscillators and Long-Term Plasticity

The olivocerebellar system plays a central role in motor learning, crucially contributing to the coordination, precision and accurate timing of movements. The system is formed by Purkinje cells (PC), the Deep Cerebellar Nucleus (DCN) and Inferior Olive (IO). Its input activate the PC which produces simple (SS) and complex spikes (CS). The latter...

Electrophysiological Evaluation of the Continuity and Transmurality of Surgical Ablation Lesions in Ex Vivo Perfused Porcine Hearts by Unipolar High-Resolution Mapping

Introduction: Currently, there is no method available for intra-operative evaluation of the completeness (transmurality and continuity) of surgical ablation lesions. This study aimed to investigate the changes in electrogram characteristics and activation patterns caused by different (non)transmural and (dis)continuous ablation lesions in ex...