Elisa Pitzalis
Department of Electrical and Electronic Engineering, University of Cagliari
My thesis project for the B.Sc. in Biomedical Engineering is focused on the design and development of a tool for the annotation of post-ischemic ventricular tachycardia bipolar electrograms (EGMs). Specifically, the software will allow clinical experts to visualize and classify EGMs, and eventually perform the delineation of abnormal ventricular potentials (AVPs). The project also includes statistical analysis of the collected data, although the ultimate goal is the creation of the first multi-annotated AVP dataset, to be later published.
Christian Cossu
Department of Electrical and Electronic Engineering, University of Cagliari
My thesis project for the B.Sc. in Biomedical Engineering is focused on the study of the pathological deflection in intracardiac electrograms acquired on patients affected by post-ischaemic ventricular tachycardia. This objective will be pursued using the signals acquired during electroanatomical mapping procedures by the group of Graziana Viola (MD EP staff at Santissima Annunziata Hospital in Sassari) and leveraging on deep learning techniques.
Angelica Congiu
Department of Electrical and Electronic Engineering, University of Cagliari
My thesis project for the B.Sc. in Biomedical Engineering is focused on the development and test of an experimental protocol for studying the binocular movements during both an active motor training and a passive motor training involving moving visual stimuli. The goal is to evaluate and compare the role of the eyes during these two different upper limb movement experiences.
Grazia Corrias
Department of Electrical and Electronic Engineering, University of Cagliari
My thesis project for the B.Sc. in Biomedical Engineering is focused on the study, development, and benchmarking of solutions for acoustic startle reflex detection and analysis in humans. By exploiting previous experiences and commercial tools, I’ll try to propose novel solutions in order to reduce noise and improve the quality of recordings.
Maria Mura
Department of Electrical and Electronic Engineering, University of Cagliari
My thesis project for the B.Sc. in Biomedical Engineering is focused on the study of Heart Rate Variability, computed through a novel statistical approach such as the Point Process, in subjects affected by REM Sleep Behavior Disorder (RBD). The goal is to assess the presence of a significant statistical difference between these subjects, a control group, and a group of patients affected by both RBD and Parkinson’s disease, across different sleep stages.
Elisa Facchini
Department of Electrical and Electronic Engineering, University of Cagliari
My thesis project for the B.Sc. in Biomedical Engineering is focused on studying Heart Rate Variability in patients affected by Parkinson’s disease and/or REM sleep behavior disorder (RBD). In order to do so, I will analyze the patient’s ECG, by the use of conventional linear and nonlinear indexes.
Giulia Olla
Department of Industrial and Information Engineering, University of Pavia
My thesis project for the M.Sc. in Bioengineering is focused on the development and validation of a library of visual feedback perturbations of hand movements a virtual reality environment. The developed perturbations will be tested in a motor adaptation protocol for the upper limb, in which the ability of typical subjects to dynamically adapt to such perturbations will be assessed.
Enrico Ariu
Department of Industrial and Information Engineering, University of Pavia
My thesis project for the M.Sc. in Bioengineering is focused on the development and validation of a motor task for the upper limb in a virtual reality environment, in which the visual feedback of the hand is manipulated through a function of muscle activation acquired in real-time during the exercise by custom wearable systems.
Simone Gregni
Department of Electrical and Electronic Engineering, University of Cagliari
My thesis project for the B.Sc. in Biomedical Engineering is focused on the application of various algorithms already developed and presented in the scientific literature for the extraction of the fetal component from non-invasive, multichannel abdominal recordings. The goal is to compare the performance of these algorithms, in terms of fetal QRS detection capabilities, on a real dataset of electrophysiological signals acquired at different gestational ages.
Former projects
Matilde Farci
“Measurement and evaluation of eye movements in perceptual tasks with complex visual stimuli?”
Sara Collu
“Application of adaptive filtering to the extraction of fetal ECG signals from non-invasive recordings”
Alessandro Garau
“Morphological characterization of the electrocardiographic signal based on the heart rate by means of dynamic time warping”
Damiano Virdis
“Study of heart rate variability in idiopathic and parkinsonian subjects with REM sleep behavioural disorder”
Vanessa Selis
“Validation on healthy participants of the LiBRa home telerehabilitation system”
Carla Secchi
“Delineation of abnormal intracardiac potentials for the electrophysiological study of the post-ischaemic ventricular tachycardia”
Martina Oro
“Development of application for the collection of post-mortem physiological parameters”
Sonia Massa
“Study and Matlab implementation of software modules for the study of eye movements”
Chiara Porcu
“Application of the empirical mode decomposition to the study of ventricular intracardiac electrograms”
Stefano Deriu
“Development of an interactive virtual environment responsive to the heart rate changes”
Sara Belloni
“Development of a framework for the application of visuomotor perturbations in reaching tasks”
Gabriele Fragiacomo
“Development of a smart garment based on textile electrodes and inertial sensors for virtual-reality-based neurorehabilitation”
Maria Elena Lai
“Analysis of signals recorded by Empatica E4 during neuropsychological tasks in children with autism spectrum disorders” (B.Sc in Biomedical Engineering, University of Cagliari)
Michela Lusso
“Dynamic time warping for the comparison and adaptation of the cardiac cycle morphology at different frequencies” (B.Sc in Biomedical Engineering, University of Cagliari)
Marco Orrù
“Supervised artificial intelligence applications for the identification of arrhythmogenic substrates in post-ischemic ventricular substrate-mapping and ablation procedures” (M.Sc. in Computer Engineering, Cybersecurity and Artificial Intelligence, University of Cagliari)