Medicine and Surgery HT

Activity type

Attività formative affini o integrative

SSD

ING-INF/02

Year

2nd year

Semester

2nd semester

CFU

4

Hours distribution

50 classroom hours

Lecturers

MICAELA LIBERTI

Activity type

Attività formative affini o integrative

SSD

ING-INF/06

Year

2nd year

Semester

2nd semester

CFU

4

Hours distribution

50 classroom hours

Lecturers

FEBO CINCOTTI
PIETRO ARICÒ

Remember
● Recognize the main types of biosignals (EEG, ECG, EDA, PPG, EOG).
● Recall the fundamental characteristics of biomedical measurement systems (transducers, amplifiers, analog filters, ADCs).
● List the main quantities and parameters of signals in the time and frequency domains.
● Basic knowledge of electromagnetic fields, including the fundamental laws of electromagnetism, the law of conservation of energy, the simplest wave phenomena, and the basics of distributed-parameter circuit theory.
Understand
● Interpret the basic physiology underlying the biomedical signals addressed.
● Explain the concepts of noise, signal-to-noise ratio (SNR), and filtering.
● Give examples of the differences between various types of signal transformations (Fourier, STFT, Wigner-Ville).
● Compare different parametric and non-parametric analysis methodologies.
● Acquire essential tools for understanding the different biomedical applications of electromagnetic fields. Apply ● Basics for performing filtering, transformation, and spectral analysis operations of biomedical signals in MATLAB, through shared code examples. ● Use algorithms for extracting physiological parameters available in open access toolboxes (e.g., HRV, EBR, SCL, SCR). ● Be able to use electromagnetic theory and related analytical tools to build simplified models of electromagnetic problems. Analyze ● Differentiate the tonic and phasic components of the EDA signal through decomposition. ● Extract parameters from ECG/PPG/EOG (e.g., HR, HRV, EBR) using open access toolboxes. ● Organize experimental data and extract features of interest using processing algorithms covered in class. ● Attribute physiological meaning to parameters extracted from biomedical signals.
● Be able to use these models to assess and quantify the required quantities.

Remember
● Recognize the main types of biosignals (EEG, ECG, EDA, PPG, EOG).
● Recall the fundamental characteristics of biomedical measurement systems (transducers, amplifiers, analog filters, ADCs).
● List the main quantities and parameters of signals in the time and frequency domains.
● Basic knowledge of electromagnetic fields, including the fundamental laws of electromagnetism, the law of conservation of energy, the simplest wave phenomena, and the basics of distributed-parameter circuit theory.
Understand
● Interpret the basic physiology underlying the biomedical signals addressed.
● Explain the concepts of noise, signal-to-noise ratio (SNR), and filtering.
● Give examples of the differences between various types of signal transformations (Fourier, STFT, Wigner-Ville).
● Compare different parametric and non-parametric analysis methodologies.
● Acquire essential tools for understanding the different biomedical applications of electromagnetic fields. Apply ● Basics for performing filtering, transformation, and spectral analysis operations of biomedical signals in MATLAB, through shared code examples. ● Use algorithms for extracting physiological parameters available in open access toolboxes (e.g., HRV, EBR, SCL, SCR). ● Be able to use electromagnetic theory and related analytical tools to build simplified models of electromagnetic problems. Analyze ● Differentiate the tonic and phasic components of the EDA signal through decomposition. ● Extract parameters from ECG/PPG/EOG (e.g., HR, HRV, EBR) using open access toolboxes. ● Organize experimental data and extract features of interest using processing algorithms covered in class. ● Attribute physiological meaning to parameters extracted from biomedical signals.
● Be able to use these models to assess and quantify the required quantities.

Module: Analysis of biomedcial data and signals
Basics of mathematics and physics


Module: Fundamentals of electromagnetic fields
N/D

Module: Analysis of biomedcial data and signals
Integral theorems of electromagnetism
Maxwell’s equations
Properties of material media
Properties of biological tissues
Boundary conditions
Poynting’s theorem
Electromagnetic waves
Transmission lines
Therapeutic techniques based on the use of electromagnetic fields



Module: Fundamentals of electromagnetic fields
N/D

Module: Analysis of biomedcial data and signals
Gerosa, Lampariello, Lectures on Electromagnetic Fields, Ingegneria 2000 Editions, Rome, 2006
Lecture notes
Additional materials provided by the instructor, downloadable from the e-learning website



Module: Fundamentals of electromagnetic fields
N/D

Module: Analysis of biomedcial data and signals
N/D
Module: Fundamentals of electromagnetic fields
N/D

Module: Analysis of biomedcial data and signals
Teaching is developed in presence. The theoretical lessons are flanked with some exercises as well as lectures from known experts


Module: Fundamentals of electromagnetic fields
N/D

Module: Analysis of biomedcial data and signals
The presence at the lessons is "Optional"


Module: Fundamentals of electromagnetic fields
N/D

TBD

Module: Analysis of biomedcial data and signals
Examples of questions:
Electromagnetic waves
Waveguides
Modes in a waveguide
…




Module: Fundamentals of electromagnetic fields
N/D

Module: Analysis of biomedcial data and signals

• Recap of differential operators and Elettromagnetism fundamental theorms (9 hours)
  • Books: pdf files downloadable from elearning 


• Basic concepts of electromagnetism (Maxwell’s equations, EM properties, boundary conditions, Poynting’s theorem) (15 hours)
  • Books: pdf files downloadable from elearning 


• Low-frequency therapeutic applications (NIBS) (8 hours)
  • Books: pdf files downloadable from elearning 


• Advanced concepts of electromagnetism (Plane waves, transmission lines) (12 hours)
  • Books: pdf files downloadable from elearning 


• Examples of biomedical applications
  • Books: pdf files downloadable from elearning