The course subject covers the generation, acquisition and analysis of signals originating from biological systems, through the study of the fundamental principles of electrophysiology at the cellular level, as well as the acquisition devices and processing techniques at hardware and software levels. A wide range of biosignals is presented, such as electromyogram, electroneurogram and electrooculogram, emphasizing on signals originating from the brain and the heart. Specifically, the anatomy and physiology of the brain are presented in relation to the generation of the electroencephalogram (EEG), as well as acquisition and processing procedures aimed at studying features such as evoked potentials. Similarly, the physiology of the heart is presented, along with the association between its rhythmic function (blood flow, systolic/diastolic pressure, ejection fraction) and the generation and acquisition of the electrocardiogram (ECG). In addition, the course includes fundamental principles of medical imaging, with an emphasis on magnetic resonance imaging and its use in studying brain activity, including the derivation of networks for the analysis of anatomical and functional connectivity. For all biosignals, appropriate preprocessing techniques for noise removal are presented, along with the application of artificial intelligence methods (including deep learning) and the subsequent deployment of biomedical engineering systems in clinical practice, leveraging big data.
- Teacher: Γεώργιος Ματσόπουλος
ECTS : 4
Study Load : theory 3 hrs
Language : el, en
Learning Outcomes : Upon completion of the course, students will be familiar with the various categories of biosignals, their generation through human physiological function, and their utilisation in research and clinical settings. They will understand the fundamental procedures and the required equipment for biosignal acquisition, as well as the steps and techniques required to improve signal quality and conduct subsequent analysis aimed at supporting real-world problems and applications relating to diagnosis, prognosis, treatment, and the broader management of medical data.