Courses
The course is based on experiential learning and hands-on group projects focused on learning by doing. Students access advanced biomedical laboratory instrumentation to understand how signals are acquired before being processed and analyzed. The emphasis is on bio-oriented applications and the design of technologies for biomedical and healthcare contexts.
Instructor: Margherita Matarrese, Pierpaolo Fucile
The course combines theory with experiential learning through hands-on activities and group projects. Students analyze signals from different domains, focusing on information extraction and critical comparison of processing techniques. Applications span human-centered and industrial contexts, supporting the design of signal-based technologies.
Instructor: Margherita Matarrese, Pierpaolo Fucile
This course adopts a hands-on and project-based approach, centered on learning by doing in multidisciplinary teams. Medical and engineering students work together on real biomedical signal processing problems using data acquired through advanced laboratory instrumentation. The course promotes integration between medicine and engineering, linking signal acquisition to processing and clinical interpretation.
Instructors: Margherita Matarrese, Leandro Pecchia
The course is built on experiential and hands-on learning, with group projects based on learning by doing. During the first semester, engineering students collaborate with MedTech students, fostering multidisciplinary integration between engineering and medicine. Students have access to advanced research laboratory instrumentation to understand how biomedical signals are acquired and processed, with a final focus on advanced signal processing technologies for healthcare applications.
Instructors: Margherita Matarrese, Pierpaolo Fucile
MedTech design, regulation, sustainability and innovation
The course aims to provide students with theoretical knowledge and practical skills to understand and address the challenges related to the design, regulation, sustainability, and innovation of medical devices and health technologies (MedTech), within a rapidly evolving European and global context.
Students will acquire an integrated and interdisciplinary perspective on the life cycle of biomedical technologies, from the early stages of ideation and co-design to end-of-life management and reuse, encompassing regulation, assessment, manufacturing, and market adoption. The course is designed to train professionals capable of effectively engaging with diverse stakeholders—including clinicians, engineers, regulatory authorities, industry, and patients—with particular attention to environmental sustainability, responsible innovation, and regulatory compliance.
Instructors: Joseph Lovecchio, Karina Ovejero Paredes
Medical devices: design, regulation, sustainability and innovation
The course aims to provide students with the knowledge and practical awareness needed to understand and manage the challenges associated with medical devices and health technologies in clinical practice, within a rapidly evolving European and global healthcare context. Particular emphasis is placed on the adoption, evaluation, and responsible use of medical technologies.
Students will develop an integrated and interdisciplinary understanding of the life cycle of biomedical technologies, from clinical need identification and co-design to regulatory approval, clinical evaluation, implementation in healthcare settings, and end-of-life management. The course prepares students to effectively interact with regulatory authorities, industry partners, and patients, while addressing key issues related to patient safety, regulatory compliance, environmental sustainability, and responsible medical innovation.
Instructors: Leandro Pecchia, Joseph Lovecchio, Karina Ovejero Paredes
Applications of GenAI and deep learning for health and wellbeing
The course focuses on practical applications of generative AI and deep learning in health and wellbeing, with particular attention to large language models, multimodal AI, and digital health solutions. Through real-world use cases such as clinical decision support, patient monitoring, and AI-assisted healthcare services, students gain hands-on insight into how advanced AI systems are deployed in modern healthcare.
Instructors: Luca Bacco e Mario Merone
Advanced processing and AI for biomedical data, signals and images
The course explores advanced techniques for the analysis of biomedical data, signals, and images, with a strong focus on the use of artificial intelligence and machine learning. Its innovative nature lies in a data-driven approach applied to real clinical problems, enabling students to acquire skills that are directly applicable to research and digital healthcare.
Instructors: Luca Bacco e Mario Merone
Master In Applied Artificial Intelligence Engineering
A practical program, built on real-world experiences of Artificial Intelligence–driven transformation, led by professionals who have already implemented AI in complex organizations, transforming multiple sectors across the globe.
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.