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 ...

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 ...

In today's audio production and reproduction as well as in music performance practices it has become common practice to alter reverberation artificially through electronics or electro-acoustics. For music productions, radio plays, and movie soundtracks, the sound is often captured in small studio spaces with little to no reverberation to save real estate and to ensure a controlled environment such that the artistically intended spatial impression can be added during post-production. Spatial sound reproduction systems require flexible adjustment of artificial reverberation to the diffuse sound portion to help the reconstruction of the spatial impression. Many modern performance spaces are multi-purpose, and the reverberation needs to be adjustable to the desired performance style. Employing electro-acoustic feedback, also known as Reverberation Enhancement Systems (RESs), it is possible to extend the physical to the desired reverberation. These examples demonstrate a wide range of applications ...

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 ...

The electrocardiogram or ECG is a relatively easy-to-record signal that contains an enormous amount of potentially useful information. It is currently mostly being used for screening purposes. For example, pre-participation cardiovascular screening of young athletes has been endorsed by both scientific organisations and sporting governing bodies. A typical cardiac examination is taken in a hospital environment and lasts 10 seconds. This is often sufficient to detect major pathologies, yet this small sample size of the heart’s functioning can be deceptive when used to evaluate one’s general condition. A solution for this problem is to monitor the patient outside of the hospital, during a longer period of time. Due to the extension of the analysis period, the detection rate of cardiac events can be highly increased, compared to the cardiac exam in the hospital. However, it also increases the likelihood of ...

To preserve the privacy of patients and service providers in biomedical signal processing applications, particular attention has been given to the use of secure multiparty computation techniques. This thesis focuses on the development of a privacy preserving automatic diagnosis system whereby a remote server classifies a biomedical signal provided by the patient without getting any information about the signal itself and the final result of the classification. Specifically, we present and compare two methods for the secure classification of electrocardiogram (ECG) signals: the former based on linear branching programs and the latter relying on neural networks. Moreover a protocol that performs a preliminary evaluation of the signal quality is proposed. The thesis deals with all the requirements and difficulties related to working with data that must stay encrypted during all the computation steps. The proposed systems prove that carrying out ...

Over the last decade there has been an increasing interest in solutions for the continuous monitoring of health status with wireless, and in particular, wearable devices that provide remote analysis of physiological data. The use of wireless technologies have introduced new problems such as the transmission of a huge amount of data within the constraint of limited battery life devices. The design of an accurate and energy efficient telemonitoring system can be achieved by reducing the amount of data that should be transmitted, which is still a challenging task on devices with both computational and energy constraints. Furthermore, it is not sufficient merely to collect and transmit data, and algorithms that provide real-time analysis are needed. In this thesis, we address the problems of compression and analysis of physiological data using the emerging frameworks of Compressive Sensing (CS) and sparse ...

Congenital heart defects are the leading cause of birth defect-related deaths. The fetal electrocardiogram (fECG), which is believed to contain much more information as compared with conventional sonographic methods, can be measured by placing electrodes on the mother’s abdomen. However, it has very low power and is mixed with several sources of noise and interference, including the strong maternal ECG (mECG). In previous studies, several methods have been proposed for the extraction of fECG signals recorded from the maternal body surface. However, these methods require a large number of sensors, and are ineffective with only one or two sensors. In this study, state modeling, statistical and deterministic approaches are proposed for capturing weak traces of fetal cardiac signals. These three methods implement different models of the quasi-periodicity of the cardiac signal. In the first approach, the heart rate and its ...

The purpose of this thesis is to present an original computer model of electrical propagation in a realistic model of human atria for the study of atrial arrhythmias. In the last years, the ever– increasing computer power has permitted the development of numerical models of cardiac electrical propagation in structures of increasing sizes. Recently, it has become possible to simulate propagations in whole parts of the human heart. However, modeling arrhythmias is still a numerical challenge since the simulation of several seconds of cardiac activity is required. In that case, the finite power of computers imposes trade–offs to limit the complexity of the models. This work demonstrates how models specifically targeted for long–term arrhythmias simulations can be efficiently constructed. The atrial anatomy is of primary importance in these developments, since the limited atrial wall thickness allows structural simplifications that would ...

The subject of this PhD thesis is the efficient and robust processing and analysis of the audio recordings that are derived from a call center. The thesis is comprised of two parts. The first part is dedicated to dialogue/non-dialogue detection and to speaker segmentation. The systems that are developed are prerequisite for detecting (i) the audio segments that actually contain a dialogue between the system and the call center customer and (ii) the change points between the system and the customer. This way the volume of the audio recordings that need to be processed is significantly reduced, while the system is automated. To detect the presence of a dialogue several systems are developed. This is the first effort found in the international literature that the audio channel is exclusively exploited. Also, it is the first time that the speaker utterance ...

This study compares the performances of different classification schemes and fusion techniques for target differentiation and localization of commonly encountered features in indoor robot environments using sonar sensing. Differentiation of such features is of interest for intelligent systems in a variety of applications such as system control based on acoustic signal detection and identification, map-building, navigation, obstacle avoidance, and target tracking. The classification schemes employed include the target differentiation algorithm developed by Ayrulu and Barshan, statistical pattern recognition techniques, fuzzy c-means clustering algorithm, and artificial neural networks. The fusion techniques used are Dempster-Shafer evidential reasoning and different voting schemes. To solve the consistency problem arising in simple majority voting, different voting schemes including preference ordering and reliability measures are proposed and verified experimentally. To improve the performance of neural network classifiers, different input signal representations, two different training algorithms, and ...

Obstructive sleep apnea (OSA) is the most prevalent sleep related breathing disorder, nevertheless subjects suffering from it often remain undiagnosed due to the cumbersome diagnosis procedure. Moreover, the prevalence of OSA is increasing and a better phenotyping of patients is needed in order to prioritize treatment. The goal of this thesis was to tackle those challenges in OSA diagnosis. Additionally, two main algorithmic contributions which are generally applicable were proposed within this thesis. The binary interval coded scoring algorithm was extended to multilevel problems and novel monotonicity constraints were introduced. Moreover, improvements to the random-forest based feature selection were proposed including the use of the Cohen’s kappa value, patient independent validation, and further feature pruning steered by the correlation between features. These novel methods were applied together with classification and feature selection methods from the literature to improve the OSA ...

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, ...

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 ...

Electrocardiography (ECG) is the standard method for assessing the state of the cardiovascular system non-invasively. In the context of magnetic resonance imaging (MRI) the ECG signal is used for cardiac monitoring and triggering, i.e., the acquisition of images synchronized to the cardiac cycle. However, ECG acquisition is impeded by the static and dynamic magnetic fields which alter the measured voltages and may reduce signal-to-noise ratio (SNR), leading to false alarms during cardiac monitoring or to image artifacts during cardiac triggering. A major source of noise is the magnetohydrodynamic (MHD) effect as it is proportional to field strength and represents a key challenge in application of ultra-high-field (UHF) MRI >=7 T. In this work, two approaches for overcoming these limitations are proposed: i) Development of a hardware and software system based on the principal of photoplethysmography imaging (PPGi) as an optical ...