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Scheda Riassuntiva
Anno Accademico 2016/2017
Tipo incarico Dottorato
Insegnamento 050612 - BIOSIGNAL PROCESSING 4 ALL: APPLICATIONS IN AFFECTIVE-COMPUTING, BIOMETRIC AND NEUROMARKETING
Cfu 5.00 Tipo insegnamento Monodisciplinare
Docenti: Titolare (Co-titolari) Mainardi Luca (Matteucci Matteo)

Corso di Dottorato Da (compreso) A (escluso) Insegnamento
MI (1300) - SCUOLA DI DOTTORATOAZZZZ050612 - BIOSIGNAL PROCESSING 4 ALL: APPLICATIONS IN AFFECTIVE-COMPUTING, BIOMETRIC AND NEUROMARKETING

Programma dettagliato e risultati di apprendimento attesi

MISSION and GOAL

 

There is a growing need for expertise in physiological signal analysis for non-clinical applications covering different engineering areas. To answer the need, the course provides PhD students (from several PhD programs) with the basic knowledge on biomedical signals, their features and the basic tools used to make sense out of them.

 

 

DETAILED PROGRAM

 

An introduction to Biosignals. Description of the main information content of principal biosignals such as Electrocardiogram (ECG), Electrencephalogram (EEG) and evoked potentials, Electromigrams (EMG), Blood Volume Pulse (BVP), Galvanic Skin Conductance and Pupil Diameter. Properties and characteristic of the signals and their relevant features for engineering applications. Biomedical signal processing methods for physiological wave detection and feature extraction in time, frequency and time-frequency domains. Variability measurements and quantification of biosignal oscillations.  Basics of non-linear analysis and irregularity quantification in physiological signals. Description of available signal processing tools and databases. (9 Hours).

 

Basic of pattern recognition. Methods for features selection, features rejection and feature reduction. Classification through biosignal features: peculiarity and problems. Pattern recognition tools. (6 hours)

 

Seminars. The course is complemented by a series of seminars designed to show novel, non-clinical biomedical signal processing applications. They includes 3-hours lesson on the following topics:

 

S1: Who are you? Biometric human identification through biosignals.  

S2: What do you like? Biomedical signal processing for Neuromarketing applications. 

S3: How do you enjoy it? Affective computing for improving game engagement through biosignal measures.

S4: How do you feel? I-Drive: monitoring driver status and comfort through biosignal processing.

S5: How can I help you? Brain signal interpretation as assistive technology.

 

 

LEARNING OBJECTIVES 

 

The students will learn the main properties of biomedical signal, their processing methods and they will be aware of the main information that can be extracted from them. The seminar activities will provide successful example of applications  in many engineering areas ranging from biometrics, affective computing and Neuromarketing. We expect the student will gain the basic knowledge of signal processing and tools and it will be able to properly apply them in different application fields.


Note Sulla Modalità di valutazione

Students are asked to prepare an oral presentation about one of the applications presented during the course or even proposed by the student himself/herself. They will be required to introduce the problem, identify the requirements, present (or design) a possible solution involving biomedical signal processing methods. Skill in defining the requirements, the signal processing methods involved and the performed analysis will be evaluated. 


Intervallo di svolgimento dell'attività didattica
Data inizio
Data termine

Calendario testuale dell'attività didattica

Lessons will be scheduled within a single week.

 

Mon, June 19th,

10:00-13:00  Intoduction to Biosignals. Features and Characteristics.

14:30-17:30  Biomedical Signal Processing Methods I: time and frequncy domain features, wave detections.

 

Tue, June 20th

10:00-13:00  Biomedical Signal Processing Methods II: Variability and non-linearity

14:30-17:30  Basic of pattern recognition I: Methods for features selection, features rejection and feature reduction.

 

Wed, June 21th

10:00-13:00 Basic of pattern recognition II: Classification through biosignal features: peculiarity and problems. 

14:30-17:30 Seminar S1: Who are you? Biometric human identification through biosignals.   

 

Thu, June 22th

10:00-13:00 Seminar S2: What do you like? Biomedical signal processing for Neuromarketing applications. 

14:30-17:30 Seminar S3: How do you enjoy it? Affective computing for improving game engagement through biosignal measures.

 

Fri, June 23th

10:00-13:00 Seminar S4: How do you feel? I-Drive: monitoring driver status and comfort through biosignal processing.

14:30-17:30 Seminar S5: How can I help you? Brain signal interpretation as assistive technology.

 


Bibliografia
Risorsa bibliografica facoltativaL. Mainardi and M. Matteucci, Slides and Lectures Notes
Risorsa bibliografica obbligatoriaL . Sornmo and P. Laguna, Bioelectrical Signal Processing in Cardiac and Neurological Applications, Editore: Elsevier, Anno edizione: 2005, ISBN: 9780124375529
Risorsa bibliografica obbligatoriaRangaraj M. Rangayyan, Biomedical Signal Analysis, Editore: Wiley-IEEE Press, Anno edizione: 2015, ISBN: 978-0-470-91139-6
Risorsa bibliografica obbligatoriaRichard O. Duda, Peter E. Hart, David G. Stork, Pattern Classification, Editore: Wiley, ISBN: 978-0-471-05669-0
Risorsa bibliografica obbligatoriaGareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani, An Introduction to Statistical Learning, Editore: Springer, Anno edizione: 2013, ISBN: 978-1461471370 http://www-bcf.usc.edu/~gareth/ISL/

Software utilizzato
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Mix Forme Didattiche
Tipo Forma Didattica Ore didattiche
lezione
30.0
esercitazione
0.0
laboratorio informatico
0.0
laboratorio sperimentale
0.0
progetto
6.0
laboratorio di progetto
0.0

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese

Note Docente
schedaincarico v. 1.10.1 / 1.10.1
Area Servizi ICT
07/11/2024