ACADEMY

EDUCATION AND TRAINING

BCI WORKSHOPS

If your lab plans to organize a workshop or satellite event at your institution, g.tec will be happy to send a researcher who can talk about brain-computer interfaces, spike recordings, real-time physiology analysis, Virtual Reality systems, functional mapping with ECoG, and related topics. Every workshop can be booked as half-day or full-day workshop.

  • Workshop 1: Brain-computer interface
  • Workshop 2: Spike and ECoG recordings
  • Workshop 3: Coma/Consciousness assessment
  • Workshop 4: Passive functional mapping
  • Workshop 5: Stroke rehabilitation

BCI LECTURES

gtec’s BCI Lectures allow researchers, professors and users to quickly learn how to run a BCI and perform experiments. The lectures are perfectly suited for teaching because of the separation of tasks and solution manuals.

  • Lecture 1: The Electroencephalogram (EEG)
  • Lecture 2: The Brain-Computer Interface (BCI)
  • Lecture 3: The Electrocardiogram (ECG)
  • Lecture 4: Physio Observer
  • Lecture 5: Evoked Potentials (EP)
  • Lecture 6: g.Nautilus Sports

LECTURE 1: THE ELECTROENCEPHALOGRAM (EEG)

The Electroencephalogram (EEG) is a tutorial that introduces the reader to EEG recordings and analysis methods. The reader will learn how to assemble electrodes correctly, set up the recording equipment appropriately and make high-quality EEG recordings. Furthermore, several EEG experiments have to be performed, which will provide hands-on experience and understanding of state-of-the-art EEG analysis topics.

  • Average time to perform the lecture: 450 min
  • Pages of lecture: 47
  • Pages of solutions for lecture: 24

CONTENTS

  • Learn to assemble electrodes according to the 10-20 system
  • Learn to assemble electrodes with EEG caps and active electrodes
  • Test the impedance of the EEG electrodes
  • Learn how to connect the electrodes to the amplifier and to make monopolar and bipolar recordings
  • Learn how to test the recording setup
  • Learn to recognize alpha and beta rhythms
  • Learn to recognize artifacts in the EEG recording
  • Learn to eliminate artifacts from the EEG recording
  • Investigate the alpha block during a mental task
  • Investigate hemispheric differences during language and spatial processing
  • Learn how hyperventilation affects the EEG
  • Learn the EEG differences of introverts and extraverts

LECTURE 2: THE BRAIN-COMPUTER INTERFACE (BCI)

The Brain-Computer Interface (BCI) is a tutorial which introduces the reader to BCI experiments and analysis methods. The reader will learn how to analyze BCI data in off-line and on-line mode and to set up real-time Simulink models for BCI experiments. Experiments will be introduced that can be used to acquire EEG data for training the computer on subject specific patterns, and for real-time feedback to control a cursor. Several examples of parameter extraction algorithms like bandpower, Hjorth and adaptive autoregressive models (AAR) will be explained. Classification algorithms like linear discriminant analysis (LDA) and neural networks (NN) are also part of the lecture. The reader has to perform several tasks to provide experience with a range of state-of-the-art BCI processing steps.

  • Average time to perform the lecture: 465 min
  • Pages of lecture: 89
  • Pages of solutions for lecture: 28

CONTENTS

  • Learn pre-processing steps for BCI data analysis
  • Calculate the power spectrum and event-related desynchronization of EEG data
  • Extract features of the different EEG channels
  • Train different classifiers to discriminate the features
  • Compare feature extraction and classification algorithms
  • Conduct BCI experiments without feedback to get data for pattern recognition
  • Perform real-time BCI experiments with cursor feedback
  • Learn to write processing batches for fast off-line analysis
  • Extract reactive frequency components out of the EEG data
  • Modify real-time analysis models for optimal performance
  • Train yourself to reach a high BCI classification accuracy

LECTURE 3:
THE ELECTROCARDIOGRAM (ECG)

The ECG lecture is intended to give a practical entry to state-of-the-art ECG processing. The reader is confronted with common tasks of modern ECG analysis and is taught how to practically solve the problems. Each lesson starts with a theoretical part to provide enough knowledge to solve the tasks.

  • Average time to perform the lecture: 760 min
  • Pages of lecture: 58
  • Pages of solutions for lecture: 71

CONTENTS

  • Measure Einthoven-, Goldberger- and Wilson-derivations
  • Perform 12 lead derivations
  • Learn to identify and avoid artifacts in the ECG signals
  • Calculate single beat intervals and amplitudes
  • Perform automatic QRS complex detection
  • Program an off-line and on-line QRS complex detector
  • Analyze tilt table experiments
  • Detect arrhythmias and abnormalities

LECTURE 4:
EVOKED POTENTIALS (EP)

The Lecture Evoked Potentials explains the recording and analysis of auditory steady-state responses (ASSRs), the auditory P300 response and brainstem auditory evoked potentials (BAEP). Each of these methods is important in clinical electroencephalography. The auditory P300 response can also be used as interaction method within a Brain Computer Interface (BCI).

  • Average time to perform the lecture: 430 min
  • Pages of lecture: 85

CONTENTS

  • Configure the auditory stimulator correctly for EPs
  • Record and analyze P300 responses
  • Record and analyze MMN
  • Record and analyze ASSRs
  • Record and analyze BAEPs
  • Record and analyze SSEPs
  • Perform step-by-step the off-line analysis
  • Run analysis batches to evaluate the captured EPs

LECTURE 5: PHYSIOOBSERVER

This lecture explains the recording and evaluation of physiological and cognitive parameters. With biosignals like ECG, GSR, respiration, EEG, physiological parameters like heart- rate and cognitive indices like the EEG band power, it is possible to recognize various mental and physical states of a person in real-time. This leads to a better human-computer interaction and human- robot cooperation.

  • Average time to perform the lecture: 240 min
  • Pages of lecture: 65
  • Pages of solutions for lecture: 19

CONTENTS

  • Configure the physio observer to run experimental paradigms
  • Perform a circle training experiment
  • Perform high altitude medicine experiments

LECTURE 6: g.NAUTILUS SPORTS

This lecture demonstrates how the g.Nautilus wireless biosignal amplifier can be used to record EEG signals during sports exercise. It users an auditory paradigm similar to the ones presented in the Evoked potentials lecture to demonstrate the stability and low number of artefacts achievable with the g.Nautilus device during physical exercises.

  • Average time to perform the lecture: 120 min
  • Pages of lecture: 39
  • Pages of solutions for lecture: 15

CONTENTS

  • Configure the g.Nautilus device to run experimental paradigms
  • Record the EEG while the subject simultaneously performs physical exercise and follows an EP paradigm
  • Calculate the jitter in displaying the auditory stimuli and display the observed EP signals.

CUSTOMER TRAINING

g.tec’s research systems are powerful tools and open a wide range of possible applications. This is why g.tec provides training opportunities at g.tec offices in Austria, Barcelona and New York. Get a general introduction to your systems, see some basic experiments and application examples or discuss special hardware- and software solutions with our developers, programmers and application engineers. The training is most effective if you come with your own g.tec system to guarantee that all the settings are performed correctly on your system. All branches offer space for groups of up to 40 members of your team for the training. Just contact us to schedule your training. We are happy to help you plan your travel and accommodation.

  • COURSE 1: Off-line biosignal analysis (EEG, ECG, GSR, respiration) with g.BSanalyze
  • COURSE 2: Measuring biosignal data (EEG, ECG, GSR, respiration, EMG, EOG, ECoG, pulse, SpO2, etc.) with g.USBamp
  • COURSE 3: Running BCI (P300, motor imagery, SSVEP) experiments in real-time
  • COURSE 4: Measuring EPs (BAEP, ASSR, P300, N200,…)
  • COURSE 5: Extending the biosignal analysis with custom software modules under MATLAB/Simulink
  • COURSE 6: Acquiring and analyzing spikes
  • COURSE 7: Running Virtual Reality and physiology experiments
  • COURSE 8: Coma assessment and communication with BCIs
  • COURSE 9: Passive functional mapping with ECoG
  • COURSE 10: Motor rehabilitation with BCIs

WEBINARS

  • g.Nautilus fNIRS: Wireless EEG and fNIRS in one device
  • Electroencephalogram (EEG) and functional electrical stimulation (FES) systems
  • Recording bio-signals from different and multiple g.tec amplifiers
  • g.tec’s brain-computer interfaces
  • Eyetracking and EEG recording using Tobii and g.tec’s neurotechnologies
  • Simultaneous recording of multiple bio-signals
  • Optimizing deep brain stimulation (DBS) procedure
  • Combination of TMS with Simultaneous EEG recording

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UNICORN EDUCATION KIT

Unicorn Education is a complete teaching solution that is designed for schools and universities to make biomedical engineering, neuroscience, neurotechnologies and signal processing accessible to everybody. With 8 pieces of Unicorn Hybrid Black and the complete Unicorn Suite software environment, students can can quickly get started running brain-computer interface experiments with P300 or motor imagery and develop state-of-the-art BCI experiments within a few hours. Include Unicorn Education in your classes and let your students get in touch with a high-quality and modern brain-computer interface technology that is easy to use and fully programmable.

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BR41N.IO DESIGNERS' HACKATHON

The BR41N.IO Brain-Computer Interface Designers’ Hackathon teaches current and future developments and unlimited possibilities of Brain-Computer Interfaces in creative or scientific fields. BR41N.IO aims to help engineers, programmers and designers understand brain-computer interface technology and how artificial intelligence, life science, art, technology and neuroscience come together, leading to new BCI applications. They learn to build and program their own fully functional EEG-based BCI to control external devices, robots or different applications.¬†Participation only requires basic knowledge in Brain-Computer Interfaces, machine learning, programming or design. Required systems and software will the provided.

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