Courses
Biomedical Signal Processing is an annual course (10 CFU) within CdL in Biomedical Engineering (L8 – ENG) aiming to introduce principles, methods, and tools of engineering and physics for signal processing in medicine and biology. This course provides future biomedical engineers with a solid foundation in methods for extracting, processing, and presenting biomedical signals to derive meaningful information for prognosis, diagnosis, and health monitoring. It covers the principles underlying biomedical signal generation and interpretation, and the application of techniques to extract relevant information from these signals. Additionally, the course imparts essential principles for designing healthcare technologies focused on signal processing.
Analisi dei Segnali: Teoria e Applicazioni per la persona e per l’industria è un corso semestrale (6 CFU) del curriculum in Sistemi Intelligenti del CdL Ingegneria Industriale (L-9). Lo scopo del corso è fornire i principi alla base della generazione e dell’interpretazione dei segnali di varia natura fornendo una conoscenza avanzata dell’elaborazione del segnale. Si affrontano i metodi per estrarre informazioni rilevanti dai segnali e valutare criticamente varie tecniche di elaborazione del segnale al fine di fornire i principi per la progettazione di tecnologie per l’elaborazione del segnale.
Il corso di Elaborazione dei segnali digitali e delle Immagini nel CdLM in Ingegneria Biomedica (LM21) fornisce i principi, metodi e strumenti analitici e computazionali necessari per affrontare problemi legati all’elaborazione dei segnali a tempo discreto e delle immagini digitali. Il corso comprende aspetti generali legati al campionamento e quantizzazione, lo studio dei segnali e immagini nel dominio della frequenza e aspetti legati al Computer Vision, tra cui l’estrazione delle feature e l’interpretazione delle immagini.
The course of Biomedical Research and Innovation, Management and Assessment within the CdLM in Ingegneria Biomedica (LM21) provides students with basic knowledge about the research and development process of a new product, focusing on the biomedical sector. It also covers technological innovation, specifically emphasizing the biomedical sector. Additionally, the course includes content on planning and managing research projects, protecting intellectual property, and understanding clinical trial and CE marking procedures for new biomedical technologies.
The course of Processing of Biomedical signals I within the CdLM Medicine and Surgery ‘MedTech’ (LM41 – ENG) aims to introduce principles, methods, and tools of engineering and physics for signal processing in medicine and biology. This course provides future physicians and biomedical engineers with a foundation in methods for extracting, processing, and presenting biomedical signals to derive meaningful information for prognosis, diagnosis, and health monitoring. It covers the principles underlying biomedical signal generation and interpretation, and the application of techniques to extract relevant information from these signals.
Il modulo di Bioingegneria Elettronica e Informatica nel CdLM Scienze Infermieristiche e Ostetriche (LM/SNT1) fornisce nozioni generali dei concetti propri dell’ingegneria biomedica a studenti di infermieristica. Questo modulo generale permette di comprendere le applicazioni proprie dell’ingegneria in ambito sanitario.
Bootcamp: IoT & AI for Frugal Innovation 2024
Community-centred innovation, Tech for good, Circular economy, Sustainable production
An intensive 3-week programme of lectures, labs and project work to acquire technical skills and soft skills based on industry use cases. Tutoring and teamwork are essential parts of this team learning journey. The IoT & AI Bootcamp 2024 program will focus on Frugal Innovation. Fully aligned with sustainability and circular-economy principles, Frugal Innovation refers to the process of reducing the complexity and costs of new products, methods and designs that are created for, with or by people in developing countries. Designed in collaboration with academics and professionals, this is a short and effective 3 week course based on experiential learning and practical activities.