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Technical Interfaces to the Nervous System


learning results of the module

ID study objective
L2 Methods of signal acquisition and processing in the fields of psychophysiology, clinical neurophysiology and audiology.
L3 Understanding of how technical components and systems operate at the bio-technical interface and in human-machine interfaces. Knowledge of neural and cognitive-affective parameters in brain-computer interfaces, neuroprosthetics and neurostimulation
L4 Ability to design appropriate technical solutions, taking into account the specific aspects of the interaction between technical systems and the human body
L5 The specific risks and safety requirements of medical technology, with a focus on implantable systems
L6 Fundamental principles and mechanisms of machine learning and neuro-inspired artificial intelligence (e.g. neural networks and common machine learning methods) and their applicability to practical problems. Understanding of the similarities and differences between mathematical neuron models, modern AI techniques and machine learning
L9 The ability to independently source and evaluate information. Knowledge of specific sources of information in medical research.

Module name (EN):
Name of module in study programme. It should be precise and clear.
Technical Interfaces to the Nervous System
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Neural Engineering, Master, regulation 01.10.2025
Module code: NE3203.TIN
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P213-0267
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
3V (3 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
4
Semester: 2
Mandatory course: yes
Language of instruction:
English
Assessment:
Written exam

[updated 15.06.2026]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

NE3203.TIN (P213-0267) Neural Engineering, Master, regulation 01.10.2025 , semester 2, mandatory course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
45 class hours (= 33.75 clock hours) over a 15-week period.
The total student study time is 120 hours (equivalent to 4 ECTS credits).
There are therefore 86.25 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Dr. Sebastian Markert
Lecturer:
Dr. Sebastian Markert


[updated 17.06.2026]
Learning outcomes:
By the end of the course, students will possess an interdisciplinary understanding of neuroprosthetic systems, enabling them to integrate concepts from neuroscience, biomedical engineering, and ethics to evaluate, design, and critically assess current and future neural interface technologies. The students know the individual limitations of specific interface types and can propose tailored multisensory systems.

[updated 17.06.2026]
Module content:
1   Basics
1.1 Foundations of physiology and cell biology
1.2 Glia cells and the immune reaction
1.3 Technical and electrochemical essentials
1.4 Electrical stimulation of nerve tissue
1.5 Electrode designs for the central and peripheral nervous system
 
2   Applications
2.1 Elementary interface design
2.2 Pitfalls and troubleshooting
2.3 Alternative interface types; optical, chemical, CMOS, non-invasive
2.4 Invasive, non-invasive neurostimulation
2.5 Application / active prostheses
 
3   Perspectives
3.1 Ethics and legal aspects
3.2 Trends in neuroprostheses
3.3 Science-Fiction and transhumanism
 
Phantom demonstrator for signal acquisition

[updated 17.06.2026]
Teaching methods/Media:
Lecture / Demonstrator

[updated 17.06.2026]
Recommended or required reading:
Plonsey, Malmivuo, "Bioelectromagnetism", Oxford University Press, 1995. Online available at www.bem.fi/book
Kandel, Schwartz, "Principles of Neural Science", McGraw-Hill, NY, 6th. edition, 2021.
Liang Guo Ed., "Neural Interface Engineering: Linking the Physical World and the Nervous System", Springer International Publishing, 2020.


[updated 17.06.2026]
 
[Sat Oct 31 18:07:20 CET 2026, CKEY=ntittns, BKEY=nem2, CID=NE3203.TIN, LANGUAGE=en, DATE=31.10.2026]