Characterization of the neurometabolic coupling in the premature brain using NIRS and EEG

Every year, an estimated 15 million babies are born preterm, that is, before 37 weeks of gestation. This number is rising in all countries and currently represents more than 1 in 10 babies, affecting families all over the world. During the last decades, the survival rate of prematurely born neonates has steadily increased, mainly as a result of medical and technical progress in neonatal intensive care. The very preterm infants, which represent up to 10% of the preterm infants in the EU, remain at risk for adverse outcome and neurodevelopmental disability. These maladaptive outcomes have a severe effect on the children’s quality of life and a huge economic impact on society. In order to reduce this burden and improve neonatal care in general, appropriate tools need to be developed to identify the neonates with a higher risk of adverse outcomes. ...

Hendrikx, Dries — KU Leuven


Advanced models for monitoring stress and development trajectories in premature infants

This thesis focuses on the design of various automatic signal processing algorithms to extract information from physiological signals of preterm infants. Overall, the aim was to improve the neurodevelopmental outcome of the neonate. More specifically, three main research objectives were carried out. The first objective was to describe the maturation of neonates during their stay in the neonatal intensive care unit. The second objective was to assess the stress and pain in premature infants and their impact on the development of neonates. The third objective was to predict developmental disabilities, such as autism. The first part of this thesis presents an extensive overview of various developmental models to describe the maturation of premature infants. Three main strategies were proposed. The first strategy proposed an investigation of EEG connectivity networks. A variety of functional and effective connectivity methods were combined with ...

Lavanga, Mario — KU Leuven


Advanced solutions for neonatal analysis and the effects of maturation

Worldwide approximately 11% of the babies are born before 37 weeks of gestation. The survival rates of these prematurely born infants have steadily increased during the last decades as a result of the technical and medical progress in the neonatal intensive care units (NICUs). The focus of the NICUs has therefore gradually evolved from increasing life chances to improving quality of life. In this respect, promoting and supporting optimal brain development is crucial. Because these neonates are born during a period of rapid growth and development of the brain, they are susceptible to brain damage and therefore vulnerable to adverse neurodevelopmental outcome. In order to identify patients at risk of long-term disabilities, close monitoring of the neurological function during the first critical weeks is a primary concern in the current NICUs. Electroencephalography (EEG) is a valuable tool for continuous noninvasive ...

De Wel, Ofelie — KU Leuven


Methods for functional connectivity and morphometry in neonatal neuroimaging to study neurodevelopment

Preterm birth is a major pediatric health problem that perturbs the genetically determined program of corticogenesis of the developing brain. As a consequence, prematurity has been strongly associated with adverse long-term neurodevelopmental outcome that may persist even into adulthood. Early characterization of the underlying neuronal mechanisms and early identification of infants at risk is of paramount importance since it allows better development of early therapeutic interventions aiming to prevent adverse outcomes through resilience. This dissertation aims to investigate the consequences of preterm birth on brain function and structure and their relation to adverse neurodevelopmental outcome, as well as to unveil the effect of an early music intervention on brain function. Research to date has mainly focused on the effect of early interventions on the long-term outcome but not on the effect of those interventions on brain function in preterm populations. ...

Loukas, Serafeim — Swiss Federal Institute of Technology Lausanne (EPFL)


Development of an automated neonatal EEG seizure monitor

Brain function requires a continuous flow of oxygen and glucose. An insufficient supply for a few minutes during the first period of life may have severe consequences or even result in death. This happens in one to six infants per 1000 live term births. Therefore, there is a high need for a method which can enable bedside brain monitoring to identify those neonates at risk and be able to start the treatment in time. The most important currently available technology to continuously monitor brain function is electroEncephaloGraphy (or EEG). Unfortunately, visual EEG analysis requires particular skills which are not always present round the clock in the Neonatal Intensive Care Unit (NICU). Even if those skills are available it is laborsome to manually analyse many hours of EEG. The lack of time and skill are the main reasons why EEG is ...

Deburchgraeve, Wouter — KU Leuven


Automated quantification of preterm brain maturation using electroencephalography

Around 10 percent of all human births is premature, which means that annually about 15 million babies are born before 37 completed weeks of gestation. About one third of the admissions to the Neonatal Intensive Care Unit (NICU) consists of this patient group. Due to complications, 1 million babies die from premature delivery, and it is therefore the most important cause of neonatal death. In general, premature and immature babies have a high risk for neurological abnormalities by maturation in extra-uterine life. Even though improved health care has increased the survival changes of these neonates, they are sensitive to brain damage and consequently, neurocognitive disabilities. Nowadays, critical information about the brain development can be extracted from the electroencephalography (EEG). Clinical experts visually assess evolving EEG characteristics over both short and long periods to evaluate maturation of patients at risk and, ...

Koolen, Ninah — KU Leuven


Monitoring Infants by Automatic Video Processing

This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Neonatal seizures have onset within the 28th day of life in newborns at term and within the 44th week of conceptional age in preterm infants. Their main causes are hypoxic-ischaemic encephalopathy, intracranial haemorrhage, and sepsis. Studies indicate an incidence rate of neonatal seizures of 2‰ live births, 11‰ for preterm ...

Cattani Luca — University of Parma (Italy)


Dynamic organization of human brain function and its relevance for psychosis vulnerability

The brain is the substrate of a complex dynamic system providing a remarkably varied range of functionalities, going from simple perception to higher-level cognition. Disturbances in its complex dynamics can cause an equally vast variety of mental disorders. One such brain disorder is schizophrenia, a neurodevelopmental disease characterized by abnormal perception of reality that manifests in symptoms like hallucinations or delusions. Even though the brain is known to be affected in schizophrenia, the exact pathophysiology underlying its developmental course is still mostly unknown. In this thesis, we develop and apply methods to look into ongoing brain function measured through magnetic resonance imaging (MRI) and evaluate the potential of these approaches for improving our understanding of psychosis vulnerability and schizophrenia. We focus on patients with chromosome 22q11.2 deletion syndrome (22q11DS), a genetic disorder that comes with a 30fold increased risk for ...

Zöller, Daniela — EPFL (École Polytechnique Fédérale de Lausanne)


Heart rate variability : linear and nonlinear analysis with applications in human physiology

Cardiovascular diseases are a growing problem in today’s society. The World Health Organization (WHO) reported that these diseases make up about 30% of total global deaths and that heart diseases have no geographic, gender or socioeconomic boundaries. Therefore, detecting cardiac irregularities early-stage and a correct treatment are very important. However, this requires a good physiological understanding of the cardiovascular system. The heart is stimulated electrically by the brain via the autonomic nervous system, where sympathetic and vagal pathways are always interacting and modulating heart rate. Continuous monitoring of the heart activity is obtained by means of an ElectroCardioGram (ECG). Studying the fluctuations of heart beat intervals over time reveals a lot of information and is called heart rate variability (HRV) analysis. A reduction of HRV has been reported in several cardiological and noncardiological diseases. Moreover, HRV also has a prognostic ...

Vandeput, Steven — KU Leuven


Least squares support vector machines classification applied to brain tumour recognition using magnetic resonance spectroscopy

Magnetic Resonance Spectroscopy (MRS) is a technique which has evolved rapidly over the past 15 years. It has been used specifically in the context of brain tumours and has shown very encouraging correlations between brain tumour type and spectral pattern. In vivo MRS enables the quantification of metabolite concentrations non-invasively, thereby avoiding serious risks to brain damage. While Magnetic Resonance Imaging (MRI) is commonly used for identifying the location and size of brain tumours, MRS complements it with the potential to provide detailed chemical information about metabolites present in the brain tissue and enable an early detection of abnormality. However, the introduction of MRS in clinical medicine has been difficult due to problems associated with the acquisition of in vivo MRS signals from living tissues at low magnetic fields acceptable for patients. The low signal-to-noise ratio makes accurate analysis of ...

Lukas, Lukas — Katholieke Universiteit Leuven


Dynamics of Brain Function in Preterm-Born Young Adolescents

Preterm birth is a major risk factor for neurodevelopment impairments often only appearing later in life. The brain is still at a high rate of development during adolescence, making this a promising window for intervention. It is thus crucial to understand the mechanisms of altered brain function in this population. The aim of this thesis is to investigate how the brain dynamically reconfigures its own organisation over time in preterm-born young adolescents. Research to date has mainly focused on structural disturbances or in static features of brain function in this population. However, recent studies have shown that brain activity is highly dynamic, both spontaneously and during performance of a task, and that small disruptions in its complex architecture may interfere with normal behaviour and cognitive abilities. This thesis explores the dynamic nature of brain function in preterm-born adolescents in three ...

Freitas, Lorena G. A. — École Polytechnique Fédérale de Lausanne


Cardiorespiratory dynamics: algorithms and application to mental stress monitoring

The rate at which our heart beats, is a dynamical process enabling adaptive changes according to the demands of our body. These variations in heart rate are widely studied in so-called heart rate variability (HRV) analyses, as they contain much information about the activity of our autonomic nervous system. Variability in the heart rate arises from several processes, such as thermoregulation, hormones, arterial blood pressure, respiration, etc. One of the main short-term modulators of the heart rate is respiration. This phenomenon is called respiratory sinus arrhythmia (RSA) and comprises the rhythmic fluctuation of the heart rate at respiratory frequency. It has also widely been used as an index of vagal outflow. However, this has been widely debated as some studies have shown that the magnitude of RSA changes with respiratory rate and the depth of breathing, independently of parasympathetic activity. ...

Widjaja, Devy — KU Leuven


Spatio-temporal characterization of the surface electrocardiogram for catheter ablation outcome prediction in persistent atrial fibrillation

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia encountered in clinical practice, and one of the main causes of ictus and strokes. Despite the advances in the comprehension of its mechanisms, its thorough characterization and the quantification of its effects on the human heart are still an open issue. In particular, the choice of the most appropriate therapy is frequently a hard task. Radiofrequency catheter ablation (CA) is becoming one of the most popular solutions for the treatment of the disease. Yet, very little is known about its impact on heart substrate during AF, thus leading to an inaccurate selection of positive responders to therapy and a low success rate; hence, the need for advanced signal processing tools able to quantify AF impact on heart substrate and assess the effectiveness of the CA therapy in an objective and ...

Marianna Meo — Université Nice Sophia Antipolis


Respiratory sinus arrhythmia estimation : closing the gap between research and applications

The respiratory sinus arrhythmia (RSA) is a form of cardiorespiratory coupling in which the heart rate accelerates during inhalation and decelerates during exhalation. Its quantification has been suggested as a tool to assess different diseases and conditions. However, whilst the potential of the RSA estimation as a diagnostic tool is shown in research works, its use in clinical practice and mobile applications is rather limited. This can be attributed to the lack of understanding of the mechanisms generating the RSA. To try to explain the RSA, studies are done using noninvasive signals, namely, respiration and heart rate variability (HRV), which are combined using different algorithms. Nevertheless, the algorithms are not standardized, making it difficult to draw solid conclusions from these studies. Therefore, the first aim of this thesis was to develop a framework to evaluate algorithms for RSA estimation. To ...

Morales, John — KU Leuven


Signal and Image Processing Techniques for Image-Based Photometry With Application to Diabetes Care

This PhD thesis addresses the problem of measuring blood glucose from a photometric measurement setup that requires blood samples in the nano litre-range, which is several orders of magnitude less than the state of the art. The chemical reaction between the blood sample and the reagent in this setup is observed by a camera over time. Notably, the presented framework can be generalised to any image-based photometric measurement scheme in the context of modern biosensors. In this thesis a framework is developed to measure the glucose concentration from the raw images obtained by the camera. Initially, a pre-processing scheme is presented to enhance the raw images. Moreover, a reaction onset detection algorithm is developed. This eliminates unnecessary computation during the constant phase of the chemical reaction. To detect faulty glucose measurements, methods of texture analysis are identified and employed in ...

Demitri, Nevine — Technische Universität Darmstadt

The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.

The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.