BIO-ELECTRICITY IN HUMAN BODY: SYSTEMS AND CONTROL

1. Knowledge and understanding
Acquire knowledge of the mechanisms underlying bioelectric signal generation and propagation, electrical and dynamic models of physiological systems, and the principles of biosignal recording and analysis. Understand the fundamentals of statistical methods and classification techniques applied to biosignals.

2. Applying knowledge and understanding
Analyse the behaviour of physiological systems through electrical and dynamic models, process biosignals in the time and frequency domains, extract descriptive features, and compare signals using appropriate quantitative parameters.

3. Making judgements
Assess the suitability of analytical methods and the reliability of results based on the assumptions adopted and the characteristics of biosignals, interpreting the extracted parameters in relation to the underlying biophysical mechanisms and physiological processes.

4. Communication skills
Describe bioelectric mechanisms, models of physiological systems, and biosignal analysis results using appropriate technical terminology and graphical representations.

5. Learning skills
Apply fundamental knowledge of physiological systems and biosignals to independently explore topics not explicitly covered in the course by consulting scientific literature and technical documentation.

The course includes lectures for the acquisition and knowledge required and the carrying out activities aimed at their application. If the teaching is carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.

Basic knowledge regards: 

•  Advanced-level on physics and math
• Intermediate-level on linear systems theory and control
• Intermediate-level on programming languages

No preparatory requests for passing other courses are required.

CLASS ATTENDANCE

Attendance is not mandatory, although it is required to carry out the practical activity and the writing test.

Module 1. Neuron models and signals

• Neuron structures and functions the neurons, the action potential, the neuron communication
• The neuron electrical models and the axon transmission model
• The volume conductor field, the system to record neuron activity
• The muscle action potential.

Module 2. Bioelectrical models and signals of physiological systems

•  Peripheral Nervous System: electro-neurogram (ENG) 
•  Skeleton-Muscle System: e electromyography (EMG).
  
•  Vision System: electro-rethinogram (ERG), electro-oculogram (EOG).
•  Circulatory and Cardiac Systems: circulatory system and systemic parameters (blood pressure, blood velocity, cardiac output), heart electro/mechanical physiology, electrocardiogram (ECG), arrhythmia, and the artificial heart.

Module 3. Methodologies in bio-signal analysis 

• in time domain
• in frequency domain
• Parameter and feature extraction; notes on descriptive and inferential statistics applied to biosignals; notes on automatic biosignal classification techniques
• Case study (ECG, ENG, EMG, EOG)

COURSE TEXTBOOKS

T1) M. Bear, B. Connors, M. Paradiso, Neuroscience: Exploring the Brain, Wolters-Kluwer

T2) J. L. Semmlow, B. Griffel, Bio-signal and Medical Image Processing, CRC Press

SUGGESTED READING

T3) Webster J.G., Medical Instrumentation: Application and Design, Wiley

T4) Michael C. K. Khoo, Physiological Control System: Analysis, Simulation and Estimation, IEEE press Series on Biomedical Eng., Wiley-Interscience

METHODS FOR THE EVALUATION OF THE LEARNED KNOWLEDGE

For the exam, there are two possible assessment modalities (one excludes the other):

1. Oral exam on all course topics.

2. A practical test to be conducted during the lessons, plus an oral exam on topics not covered in the practical test (attendance is mandatory).

The assessment of learning may also be carried out remotely, if the conditions require it.

The practical activity consists of a case study based on the analysis of biomedical data. That must be submitted by the end of the course. The final grade will be determined by considering the assessment of both the oral and practical tests.

The evaluation of the oral exam during the interview will be based on the knowledge of the content, the relevance of the answers to the questions asked, the use of technical language, and the ability to make connections between the course topics.

In the second mode, for students attending the course, there is the possibility of taking a test that lasts no more than one hour. The test is optional, at the student’s discretion. It consists of a questionnaire with questions (multiple choice and/or open-ended) to assess the content not covered in the practical activity. To pass the test, it is necessary to answer correctly at least 50% of the questions. If the test is passed, at the student’s discretion, the grade obtained in the test may be considered as an oral exam evaluation or integrated by an oral discussion on specific topics agreed with the professor.  In this case, the final grade can be adjusted by considering the test and the practical test, for a maximum of three additional points.

• Describe the mechanisms of action potential generation and propagation in the neuron and the role of synapses in signal transmission.

• Describe the main electrical and mathematical models used to represent neuronal activity and signal propagation along the axon.

• Describe the generation, acquisition principles and main characteristics of ENG, EMG, ERG, EOG and ECG bioelectrical signals.

• Describe the functioning of the cardiac and circulatory systems through hemodynamic models and parameters, such as pressure, flow, velocity and cardiac flow rate.

• Illustrate the main phases of a biosignal acquisition chain, from detection to digitization and subsequent processing.

• Describe the main issues associated with biosignal acquisition, with particular reference to noise, artifacts, and filtering.

• Analyze a biosignal in the time domain, identifying and extracting significant parameters and features.

• Analyze a biosignal in the frequency domain and interpret its main spectral components.

• Analyze a case study based on biomedical data, selecting the most appropriate processing methodologies, extracting characteristic parameters and critically interpreting the results obtained.