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13M051NI - Neural Engineering

Course specification
Course title Neural Engineering
Acronym 13M051NI
Study programme Electrical Engineering and Computing
Module
Type of study master academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition none
    The goal Learn about neurophysiological acquisition and signal processing procedures, introduce neuroimaging technologies and learn about principles of robot-assisted and rehabilitation engineering.
    The outcome Ability for research and engineering work in the field of neural engineering.
    Contents
    URL to the subject page http://automatika.etf.bg.edu.rs/sr/13m051ni
    URL to lectures https://teams.microsoft.com/l/team/19%3Anr1P54jamC6ncBuywAeZ3zWEN1j8KspTe-hMxl-ePes1%40thread.tacv2/conversations?groupId=7b0255e7-c9af-476a-9b06-4137b16d31e4&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba
    Contents of lectures Neural interfaces, acquisition/processing of neural signal. Brain Computer Interface. Electrical and magnetic stimulation for restoration/augmenatation of sensory-motor functions. Neural prothesis for: hearing, vision, breathing, control of movement, urinary functions, cognitive feedback. Neurorobotics. Robotics in rehabilitation. Neuroimaging technologies. Preclinical studies.
    Contents of exercises Practical work in laboratory and clinics.
    Literature
    1. Popović, DB, Sinkjær T. Control of Movement for the Physicaly Disabled, Springer, 2000, London, U,.K
    2. Dhilon G, Horch K. (Eds.) Neuroprosthetics: Theory and Practice, 2004, World Sci Publ, New York
    3. Artemiadis P, Neuro-robotics. Trends in Augmentation of Human Performance, 2014.
    4. Ombao H, Lindquist M, Thompson W, Aston J, Handbook of Neuroimaging Data Analysis. CRC Press; 2016.
    5. Akay, Metin, ed. Handbook of neural engineering. Vol. 21. John Wiley & Sons, 2007.
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    3 1
    Methods of teaching Lectures, exercises with consulting, independent work on the project.
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures 0 Test paper 0
    Practical lessons 20 Oral examination 30
    Projects
    Colloquia 10
    Seminars 40