Information Processing

A.Y. 2019/2020
9
Max ECTS
90
Overall hours
SSD
INF/01 ING-INF/05 ING-INF/07 MED/01 SECS-S/02
Language
Italian
Learning objectives
The course aims to provide students with the technical knowledge necessary to include the operating principles of biopotential sampling systems, based on computer, methodological and statistical notions.
Expected learning outcomes
Students will be asked to know the technical knowledge necessary to understand the operating principles of biopotential sampling systems, based on computer, methodological and statistical concepts
Course syllabus and organization

Single session

Prerequisites for admission
No prior knowledge is required.
Assessment methods and Criteria
The assessment of skills by the student will be achieved through a WRITTEN TEST.
The evaluation will be expressed in thirtieths and there are currently no intermediate tests or pre-appeals.
Informatica
Course syllabus
Structure of operating systems, files, directories, drives
Programming languages, interpreters, compilers
Elements of Basic, realization of programs for the calculation of simple statistical functions
4 - Internet
Network structure
Addresses and protocols
FTP, WWW, E-mail
Structure of a web page, main instructions in html
5 - Introduction to the treatment of biological signals
Sampling, resolution, sampling theorem, aliasing
Analog and digital filters
Teaching methods
The method of delivery of the course is based on classroom lectures.
Teaching Resources
Diapositive e materiale fornite dal docente
Sistema di elaborazione delle informazioni
Course syllabus
1. Introduction
Basic concepts and history of calculating machines
Algorithms
Differences between computer and brain
Elements of neural networks; artificial intelligence
Binary code, transformation rules from decimal to binary notation
2 - Hardware
Computer hardware structure; CPU
Central memory
Magnetic and optical mass memories; USB sticks;
Input and output devices (keyboard, monitor, mouse, printers)
3 - Software
Programs; operating systems; Application SW

The course aims to provide the conceptual tools for proper management (detection and analysis) of biosignals, with particular attention to those associated with brain activity. For completeness, references will also be made to other biosignals (primarily electromyographic, cardiac and ocular). The specificities associated with spatial and temporal sampling are highlighted for each type of biosignal. The main analysis tools of biosignals are discussed both in the time domain (for example, quadratic mean and correlogram) and in the frequency domain (for example, spectral analysis with Fourier transform). As part of the analysis in the time domain, particular attention is also paid to the concept of synchronous average and the related calculation algorithm. The effects of signal truncation and sampling
itself in the time domain are deepened as part of the analysis in the frequency domain.
Teaching methods
The method of delivery of the course is based on classroom lectures.
Teaching Resources
Diapositive e materiale fornite dal docente
Misure elettriche ed elettroniche
Course syllabus
Measurement theory
The signal
The electrical signal
The measure of a signal
Electrical safety
Teaching methods
The method of delivery of the course is based on classroom lectures.
Teaching Resources
Tecnologie in medicina: principi ed applicazioni, Antonio Pedotti. Ed. Clup, 1989..
Tecnologie biomediche: esempi di applicazione ed esercizi. Pedotti A, Aliverti A, Andreoni G, Ferrigno G. Libreria Clup, 2001.
Statistica medica
Course syllabus
Measurement errors and biological variability
Identification of risk factors and prognostic factors
Evaluation of efficacy and tolerability of a therapy
Meta-analysis: principles and methods
Teaching methods
The method of delivery of the course is based on classroom lectures.
Teaching Resources
Epidemiologia e metodologia epidemologica clinica - Valsecchi e La Vecchia - Accademia Nazionale di medicina
Statistica per la ricerca sperimentale e tecnologica
Course syllabus
Introduction to scientific research in the medical field
Descriptive statistics
Introduction to inferential statistics
Structure of a scientific article
Teaching methods
The method of delivery of the course is based on classroom lectures.
Teaching Resources
Materiale fornito dal docente
Informatica
INF/01 - INFORMATICS - University credits: 3
Lessons: 30 hours
Professor: Di Rienzo Marco
Misure elettriche ed elettroniche
ING-INF/07 - ELECTRICAL AND ELECTRONIC MEASUREMENT - University credits: 1
Lessons: 10 hours
Professor: Carpinella Ilaria
Sistema di elaborazione delle informazioni
ING-INF/05 - INFORMATION PROCESSING SYSTEMS - University credits: 3
Lessons: 30 hours
Professor: Lencioni Tiziana
Statistica medica
MED/01 - MEDICAL STATISTICS - University credits: 1
Lessons: 10 hours
Statistica per la ricerca sperimentale e tecnologica
SECS-S/02 - STATISTICS FOR EXPERIMENTAL AND TECHNOLOGICAL RESEARCH - University credits: 1
Lessons: 10 hours