Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Bachelor's degree in Human Centered Medical System Engineering - Enrollment from 2025/2026The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
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2° Year activated in the A.Y. 2023/2024
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3° Year activated in the A.Y. 2024/2025
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1 module among the following| Modules | Credits | TAF | SSD |
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1 module among the following| Modules | Credits | TAF | SSD |
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Altre attività formative: lo studente può scegliere tra le 2 seguenti opzioni:
a) 2 CFU di seminari - di cui 1 CFU al 1 anno e 1 CFU al 2 anno - e 7 CFU di tirocinio al 3 anno;
b) 9 CFU di tirocinio al 3 anno. Non sono previste ulteriori opzioni.Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Modeling and Analysis of Biological Systems (2024/2025)
Teaching code
4S009891
Credits
6
Language
Italian
Also offered in courses:
- Biomedical Data and Signal Processing - Modulo A Laboratorio of the course Bachelor's degree in Computer Science
- Biomedical Data and Signal Processing - Modulo A Teoria of the course Bachelor's degree in Computer Science
Scientific Disciplinary Sector (SSD)
ING-INF/06 - ELECTRONIC AND INFORMATICS BIOENGINEERING
Courses Single
Authorized
The teaching is organized as follows:
Modulo B
Modulo A - teoria
Modulo A - laboratorio
Learning objectives
1. The teaching goals of the course will address the applicatiopin of physics and mathematical models to biological systems
Prerequisites and basic notions
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Program
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Modulo A - Teoria
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(1) Main biomedical signals and images. Origin, characteristics and acquisition of the main bioelectric signals (electroencephalographic signal - EEG, magnetoencephalographic – MEG, electrocardiographic - ECG, electromyographic - EMG, spontaneous and induced signals, evoked potentials - EP, event-related potentials - ERP). (2) Analysis techniques in the time and frequency domains. Fundamentals of digital signal processing and characterization in the time domain. Digital filtering methods, sampling, A/D conversion. Classic methods for frequency analysis; frequency bands and power spectrum, periodogram; time/frequency resolution; bispectra and coherence; feature extraction methods. Brain source imaging (direct and inverse problems for EEG and MEG signals) and functional and effective connectivity analysis methods. Applications on in-silico and real signals.
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Modulo A - Laboratorio
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The course includes a series of laboratories in the computer lab with hands-on activities mainly in MATLAB environment aimed at familiarizing students with the main analysis methods of biomedical signals and images (e.g. ECG, EMG, EEG, evoked potentials). The laboratories complement lectures by consolidating learning and developing problem-solving and hands-on practical skills in the context of bioengineering.
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Modulo B
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Introduction to the biophysics of neuronal activity. The equivalent circuit model of the cell membrane. Mathematical modeling of the membrane potential through ordinary differential equations of the single compartment model. The Hodgkin and Huxley equations for the numerical simulation of the action potential. Multi-compartmental and synaptic models. Introduction to numerical simulation of neuron and neuronal network activity. Introduction to computer technologies (Py-Neuron, Nest Simulator) that allow the simulation of neuronal circuits and extended brain regions with single cell resolution.
Bibliography
Didactic methods
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Modulo A
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Teaching methods. Regular lectures with power point presentation and blackboard, laboratory exercises and projects. The course approach is "hands on" where students will experiment the design and data analysis with the most suitable methodologies to solve real-life clinical-medical problems. Educational material will be available to students enrolled in the course on the Moodle platform. This material includes lecture presentations in PDF format and material related to laboratory activities. For further details and supplementary materials, please refer to the reference books.
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Modulo B
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Teaching is delivered through streaming lessons. The lessons will provide python programming examples. Slides will be available on the MOODLE Portal page (in compliance with copyright).
Learning assessment procedures
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Modulo A
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Assessment is conducted via oral examination preceded by a discussion on the group project assigned during the lab.
Specifically, the oral exam includes:
• A brief presentation of the lab project: graded out of ten (V1).
• Theory: graded out of twenty (V2).
Final grade: V1+V2 (1/3 lab, 2/3 theory).
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Modulo B
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The exam consists of an oral examination regards the covered topics and comprises the evaluation of the presented informatic tools alongside the implementation strategies of the main modelling systems. The interview us preceded by a short discussion of a mini-project in powerpoint discussing a free-choice topic related to the filed of neural systems modelling. In order to prepare the mini-project, a literature search work is required.
Evaluation criteria
To pass the exam, the students must show that: - they have understood the theoretical and practical concepts of the course; - they are able to use the knowledge acquired during the course to solve the assigned problems related to the analysis and modeling of biological systems; - they are able to program in MATLAB environment in the context of signal and biomedical data processing and modeling; - they are able to use the knowledge acquired during the course to manage the modeling of neuronal activity.
Criteria for the composition of the final grade
The final grade will be the average of the two grades from the two modules.
Exam language
Italiano
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