Course detail
Biofeedback Technologies
FIT-BFTaAcad. year: 2025/2026
Students will be able to study and utilize various body sensors that can be used for recording signals from human body. In addition, they will be able to utilize these sensing technologies in biofeedback applications. They will be able to analyze and interpret the body signals for both the clinical applications like improving balance as well as non-clinical applications like performance enhancement.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Aims
- To understand the principles of working of human body and basic concepts of biofeedback.
- To be able to design and implement a biofeedback protocol and record the corresponding data from body sensors.
- To be able to analyze and interpret the data acquired from body sensors and use them for various applications.
Rules for evaluation and completion of the course
Project (implementation demo, presentation, report), computer lab assignments within due dates. The minimal number of points which can be obtained from the midterm exam is 10. Otherwise, no points will be assigned to a student. In the case of a reported barrier preventing the student to defend the project or solve a lab assignment, the student will be allowed to defend the project or solve the lab assignment on an alternative date. The minimal number of points which can be obtained from the project is 20. Otherwise, no points will be assigned to a student.
Study aids
Prerequisites and corequisites
Basic literature
Donald L. Schomer, Fernando Lopes da Silva (Eds.), Niedermeyer's Electroencephalography: Basic Principles, Clinical Applications, and Related Fields, LWW, Sixth Edition, 2010, ISBN: 978-0781789424.
Donald Moss, Fredric Shaffer, Association for Applied Psychophysiology and Biofeedback: A Book of Readings, Association for Applied Psychophysiology, First Edition, 2016, ISBN: 0984297952.
Erik Peper, Biofeedback Mastery: An Experiential Teaching and Self-Training, First Edition, 2009, ISBN: 9780984297900.
F. Rieke, D. Warland, R. de Ruyter van Steveninck, and W. Bialek, Spikes: Exploring the Neural Code, MIT Press / Bradford Books, 1999, ISBN: 978-0262681087.
Guido Dornhege, Toward brain-computer interfacing, MIT Press, First Edition, 2008, ISBN: 978-0262042444.
Inna Z. Khazan, Clinical Handbook of Biofeedback, John Wiley and Sons Ltd, First Edition, 2013, ISBN: 1119993717.
Stephen Larsen, The Neurofeedback Solution, Inner Traditions Bear and Company, First Edition, 2012, ISBN: 1594773661.
Thomas Pecherstorfer, Neurofeedback and HRV Biofeedback after Stroke, VDM Verlag, First Edition, 2009, ISBN: 3639209621.
Recommended reading
M. Bear, B. Connors, and M. Paradiso, Neuroscience: Exploring the Brain, Jones & Bartlett Learning, Fourth Edition, 2020, ISBN: 978-1284211283.
Mark S. Schwartz, Biofeedback, Guilford Publications, Fourth Edition, 2016, ISBN: 1462522548.
Mike X. Cohen, Matlab for brain and cognitive scientists, MIT Press, First Edition, 2017, ISBN: 978-0262035828.
Nidal Kamel, Aamir S. Malik, EEG/ERP Analysis: Methods and Applications, CRC Press, First Edition, 2017, ISBN: 978-1138077089.
Thomas F. Collura, Technical Foundations of Neurofeedback, Routledge, First Edition, 2017, ISBN: 9781138051898.
Classification of course in study plans
- Programme MITAI Master's
specialization NSEC , 0 year of study, winter semester, elective
specialization NNET , 0 year of study, winter semester, elective
specialization NMAL , 0 year of study, winter semester, elective
specialization NCPS , 0 year of study, winter semester, elective
specialization NHPC , 0 year of study, winter semester, elective
specialization NVER , 0 year of study, winter semester, elective
specialization NIDE , 0 year of study, winter semester, elective
specialization NISY , 0 year of study, winter semester, elective
specialization NEMB , 0 year of study, winter semester, elective
specialization NSPE , 0 year of study, winter semester, elective
specialization NEMB , 0 year of study, winter semester, elective
specialization NBIO , 0 year of study, winter semester, elective
specialization NSEN , 0 year of study, winter semester, elective
specialization NVIZ , 0 year of study, winter semester, elective
specialization NGRI , 0 year of study, winter semester, elective
specialization NADE , 0 year of study, winter semester, elective
specialization NISD , 0 year of study, winter semester, elective
specialization NMAT , 0 year of study, winter semester, elective - Programme MIT-EN Master's 0 year of study, winter semester, elective
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
1. Introduction to working of Human Body: This topic will introduce the various parts of human body both anatomically and physiologically.
2. Heart Signals: This lecture is specifically dedicated to heart, its functioning and the various sensors that can be used for recording the heart signals. Further, the concept of feedback using heart rate variability will be introduced.
3. Analysis of Heart Signals: This topic will introduce various computational methods to analyze the heart signals. Both the time and frequency domain-based techniques will be taught to analyze the signals.
4. Signals from Breathing: This lecture is specifically dedicated to lungs, its functioning and the various sensors that can be used for recording the breathing signals.
5. Analysis of Breathing Signals: This topic will introduce various computational methods to analyze the breathing signals and will introduce the concept of resonance frequency as a feedback for optimal breathing.
6. Temperature and Skin Conductance: Various body sensors will be taught for recording of the skin temperature and skin conductance. The lecture will also cover their analysis and their usage in biofeedback.
7. Balance Analysis: This lecture will introduce sensors to analyze the balance and coordination of human body. The concept of coordination training as a biofeedback will be introduced in this lecture.
8. Introduction to brain: This topic will introduce the various brain (anatomical) structures (like frontal, temporal lobes etc) and their functioning.
9. Brain neural activity (EEG, ERP): The concepts of Electroencephalogram (EEG) and Event Related Potential (ERP) will be discussed in details as they are the foundation for neurofeedback which is a subset of biofeedback technologies.
10. Neurofeedback (Auditory Skills): This topic will introduce the various auditory skills and the technologies like Warnke that can be used for rapid acoustic processing, spatial hearing, pitch discrimination, and sound discrimination.
11. Neurofeedback (Neuromuscular Signals): This lecture will introduce the usage of neuromuscular signals in the rehabilitation process and the methods like Brucker Biofeedback Method.
12. Neurofeedback (Passive Stimulation): This will include topics like frequency-based training that involves training of amplitudes in frequencies of interest that correspond to the various EEG frequency bands.
13. Neurofeedback (Active Stimulation): This lecture will include topics like electrical and magnetic stimulation that are considered active stimulation methods.
Laboratory exercise
Teacher / Lecturer
Syllabus
- Record and analyze signals from heart
- Simultaneous heart rate and breathing rate measurements
- Temperature and skin conductance measurements and analysis
- Balance and coordination measurement and analysis
- Recording and analyzing brain EEG and ERP signals
Project
Teacher / Lecturer
Syllabus
Every student will choose one project from a list of approved projects that are relevant for this course. The implementation, presentation and documentation of the project will be evaluated.