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| Es werden Projektarbeiten im Umfeld des 'Berlin Brain-Computer Interface' (BBCI) Projektes angeboten ([[http://www.bbci.de]]). Ein Brain-Computer Interface ist ein System, dass es seinem Benutzer ermöglicht, einfache Computeranwendungen durch Gehirnaktivität zu steuern. Eine Projektarbeit umfasst typischerweise: (1) Planung eines EEG-Experimentes, (2) Programmierung der benötigten Software (z.B. für visuelle Reize), (3) Durchführung der Messung, (4) Analyse der aufgenommenen Daten mit statistischen Methoden, (5) Präsentation der Ergebnisse (Vortrag und Bericht). Die Arbeiten werden jeweils in kleinen Gruppen (2-3 Studierende) unter Anleitung durchgeführt. Es werden verschiedene Experimenttypen zur Auswahl gestellt. | This projects conveys experimental competences of neurotechnology exemplary. Moreover, theoretical skills in signal processing and machine learning are trained practically in hands-on experiments with self acquired data. A typical project is as follows: work out an experimental design for a given hypothesis; implement the experiment and conduct a study (including the acquisition of physiological data) with about 6 participants; investigate the acquire data with standard analysis methods and techniques from machine learning; put the results into perspective given the state-of-the-art and present them as a talk in a written report. Projects are performed in groups of 2 to 4 students. Note: This project is about the practical aspects of Brain-Computer Interfaces. The background about this field of research is given in the lecture "Brain-Computer Interfacing". |
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| Es werden gute Programmierkenntnisse sowie mathematische Grundkenntnisse vorausgesetzt. Voriger Besuch der Vorlesung Brain-Computer Interfacing ist ratsam aber nicht notwendig. | Programming skills (Matlab/Octave) and basic knowledge in signal processing and machine learning is required. Having participated in the lecture Brain-Computer Interfacing before is helpful but not required. |
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| Um einen Schein zu erhalten, muss aktiv in dem Projekt mitgearbeitet werden und die Ergebnisse durch Vortrag und Bericht dargestellt werden. | Active participation in the project and presentation of the results in a talk and in a report are required. |
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| wird auf einer ISIS Seite zur Verfügung gestellt. === Literatur === * Blankertz B, Lemm S, Treder MS, Haufe S, Müller KR, Single-trial analysis and classification of ERP components - a tutorial. Neuroimage, 56:814-825, 2011 [[http://dx.doi.org/10.1016/j.neuroimage.2010.06.048|url]] [[http://doc.ml.tu-berlin.de/bbci/publications/BlaLemTreHauMue10.pdf|pdf of draft]] * Schreuder M, Blankertz B, Tangermann M, A New Auditory Multi-class Brain-Computer Interface Paradigm: Spatial Hearing as an Informative Cue. PLoS ONE, 5(4):e9813, 2010 [[http://dx.doi.org/10.1371/journal.pone.0009813|url]] * Schreuder M, Rost T, Tangermann M, Listen, you are writing! Speeding up online spelling with a dynamic auditory BCI. Front Neuroscience, 5(112), 2011 [[https://www.frontiersin.org/Journal/Abstract.aspx?s=763&name=neuroprosthetics&ART_DOI=10.3389/fnins.2011.00112|url]] * Treder MS, Schmidt NM, Blankertz B, Gaze-independent brain-computer interfaces based on covert attention and feature attention, Open Access. J Neural Eng, 8(6):066003, 2011 [[http://dx.doi.org/10.1088/1741-2560/8/6/066003|url]] * Treder MS, Blankertz B, (C)overt attention and visual speller design in an ERP-based brain-computer interface. Behav Brain Funct, 6:28, 2010 [[http://www.behavioralandbrainfunctions.com/content/6/1/28|url]] * Venthur B, Scholler S, Williamson J, Dähne S, Treder MS, Kramarek MT, Müller KR, Blankertz B, Pyff - A Pythonic Framework for Feedback Applications and Stimulus Presentation in Neuroscience. Front Neuroscience, 4:179, 2010 [[http://dx.doi.org/10.3389/fnins.2010.00179|url]] |
Material will be provided on the web page of the course (see above). |
Project ''Brain-Computer Interfacing''
Time, Location, and other information
Module: |
MINF-IS-BCI/PJ, 6 SWS, 9 ECTS Modulbeschreibung |
Zeit: |
some common dates on Wednesdays at 10am |
otherwise up to agreement (group work; conducting experiments) |
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Location: |
TUB Marchstr. 23, Room MAR 4.044 |
First meeting to distribute topics |
Wednesday, 20|04|2016, 10am to 12 |
Lecturer: |
Benjamin Blankertz (verantwortlich) |
Entry in the course catalogue: |
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Webpage of the course: |
Inhalt
This projects conveys experimental competences of neurotechnology exemplary. Moreover, theoretical skills in signal processing and machine learning are trained practically in hands-on experiments with self acquired data. A typical project is as follows: work out an experimental design for a given hypothesis; implement the experiment and conduct a study (including the acquisition of physiological data) with about 6 participants; investigate the acquire data with standard analysis methods and techniques from machine learning; put the results into perspective given the state-of-the-art and present them as a talk in a written report. Projects are performed in groups of 2 to 4 students.
Note: This project is about the practical aspects of Brain-Computer Interfaces. The background about this field of research is given in the lecture "Brain-Computer Interfacing".
Voraussetzungen und Anforderungen
Programming skills (Matlab/Octave) and basic knowledge in signal processing and machine learning is required. Having participated in the lecture Brain-Computer Interfacing before is helpful but not required.
Active participation in the project and presentation of the results in a talk and in a report are required.
Material
Material will be provided on the web page of the course (see above).