EEG electrode placement summary, April 2015

After experimenting with different EEG amplifiers, I got more information about different EEG electrode position. And then my summary ought to be revised. Below are the revisions in my PhD note.

• Motor imagery electrode placement (wp: 03.04.2015)
• Motor imagery electrode placement (blog: 03.04.2015)
• Motor imagery electrode placement, with figures (wp: 11.09.2013)
• Motor imagery electrode placement, with figures (blog: 11.09.2013)
• Mu wave electrode placement (wp: 06.04.2015)
• Mu wave electrode placement (blog: 06.04.2015)
• P300 electrode placement (wp: 04.04.2015)
• P300 electrode placement (blog: 04.04.2015)
• SSVEP electrode placement, with figures (wp: 06.12.2013)
• SSVEP electrode placement, with figures (blog: 06.12.2013)

In my notes, I add information about CSP spatial filter because this filter is suitable with EEG amplifiers with more than 8 electrodes. CSP is Common Spatial Filter. This filter is used for motor imagery BCI involving lateralization of hand movement: left versus right, contralateral versus ipsilateral.

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Previous EEG electrode placement summary:

• EEG electrode placement summary (wp: 23.08.2014)
• EEG electrode placement summary (blog: 23.08.2014)

The EEG amplifiers, I have used so far in my PhD study at the University of Oldenburg, as well as in my master study at the University of Bremen, are below.

• mBrainTrain Smarting, a mobile EEG amplifier with 24 electrodes, since the second year of my PhD study.
• gtec MOBIlab+, a mobile EEG amplifier with maximum 8 bipolar electrodes, for the third semester of my PhD Study.
• Easymotiv, which is modified Emotiv EPOC with Easy Cap, a mobile EEG amplifier with 14 electrodes, for the first semester of my PhD study.
• TMSi Porti 7, an EEG amplifier with 32 electrodes, for my master thesis.
• gtec USBamp, an EEG amplifier with 16 electrodes, for my master project.

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Tulisan ini adalah revisi dari rangkuman posisi elektroda EEG untuk Brain-Computer Interface sebelumnya. Revisi dilakukan setelah mencoba beberapa EEG amplifier. Dalam revisi terdapat penambahan informasi tentang Common Spatial Pattern (CSP) sesuai catatan doktoral 24 November 2014.


Bremen, 18 April 2015

iscab.saptocondro
Darah Juang!

EEG electrode placement summary, August 2014

After reading the theses from my research mates from Uni Oldenburg, as well as Uni Bremen, I summarized some EEG electrode placements in my PhD note. So these are the links to my note.

• Motor imagery electrode placement (wp: 19.08.2014)
• Motor imagery electrode placement (blog: 19.08.2014)
• Motor imagery electrode placement, with figures (wp: 11.09.2013)
• Motor imagery electrode placement, with figures (blog: 11.09.2013)
• Mu wave electrode placement (wp: 19.08.2014)
• Mu wave electrode placement (blog: 19.08.2014)
• P300 electrode placement (wp: 22.08.2014)
• P300 electrode placement (blog: 22.08.2014)
• SSVEP electrode placement, with figures (wp: 06.11.2013)
• SSVEP electrode placement, with figures (blog: 06.11.2013)

SSVEP stands for steady-state visually evoked potential.

The idea is to minimize the number of EEG electrodes, which I am planning to use with my mobile EEG device. Putting electrodes to the scalp takes a lot of time. If 192 electrodes were put on whole scalp, it could took 1 hour or more and it would not be practical for the users. Also, analyzing the data from a large number of electrodes has a curse of dimensionality. I am planning to record using 8 or 16 or 24 EEG electrodes. Less is more! The EEG electrode placement which I need have been noted, so I just look into those specific electrode positions for my analysis, as well as, online signal processing.  

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Tulisan ini adalah rangkuman dari posisi elektroda EEG untuk Brain-Computer Interface (BCI) berbasis SSVEP, P300,  dan "motor imagery" atau gelombang mu, untuk bulan ini.

Bremen, 23 Agustus 2014

iscab.saptocondro
Darah Juang!

SSVEP electrode position, on my head

Since Posterous is killed by Twitter, pictures from my blog posts about standard 10-20 system are gone. The figures are not kept  by Posterous nor sent to Blogger. So I post the pictures again, which were saved by Wordpress:

• Standard 10-20 system and me, iscab
• Standard 10-20 system and me, saptocondro

I am wearing EEG cap

The pictures are about EEG electrode placement for SSVEP-BCI, according to 10-20 system (wiki: en,de). EEG is electroencephalography, which is recording of electrical signals from scalp (wiki: en,de,id). SSVEP is steady-state visually evoked potential, which is EEG signal as a response of flickering stimuli with certain frequency (wiki: en). BCI is Brain-Computer Interface (wiki: en,de).

10-20 system for EEG electrode position

The electrode position for SSVEP BCI  is Pz, PO3, PO4, O1, Oz, O2, O9 and O10. The ground is AFz and the reference is one ear lobe, either left or right. This position is used on my master thesis (book,slide).

Bremen, 6 Desember 2013

iscab.saptocondro

P.S. Now, I am thinking about EEG electrode position, for BCI, based on motor imagery.

Some scientific papers mentioning me and Brain-Computer Interface

I had involved in Brain-Computer Interface (BCI) research for 2 years. The research was done while studying in the University of Bremen. Now I have got M.Sc. degree in Information and Automation Engineering. After the end of my master study, there have been one master thesis, one master project report and 2 scientific papers related to BCI and me.

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The master project report

Title: Final Preparation of the CeBit Data

author: Ignatius Sapto Condro Atmawan (That's me!)

supervisors: Prof. Dr.-Ing Axel Gräser & Dr.-Ing Ivan Volosyak

year: 2009

place: Institute für Automatissierungstechnik (IAT), Universität Bremen, Bremen, Germany

about:

The master project is mainly about EEG data format in the IAT. The BrainRobot group from the IAT conducted experiments about steady-state visual evoked potentials (SSVEP) in CeBit 2008, Hannover and RehaCare 2008, Düsseldorf, Germany. Both experiments used different data formats. The project report mentions other alternatives of data format which have already been international standards or at least european ones: GDF, EDF, BDF and BKR.

Other data format which are not mentioned in the report can be found here:

• BioSig
• scientific data formats

The Master Thesis

Title: Improvement of Response Time in SSVEP-based Brain-Computer Interface

author: Ignatius Sapto Condro Atmawan Bisawarna (That's me!)

supervisors: Prof. Dr.-Ing Axel Gräser, Dr.-Ing Ivan Volosyak & Thorsten Lüth, Dipl.-Ing.

year: 2010

place: Institute für Automatissierungstechnik (IAT), Universität Bremen, Bremen, Germany

about:

This master thesis is about how to make SSVEP-based BCI in the IAT faster (but with less error). A few time series prediction algorithms are then used. There were simulation with MATLAB, programming with C++, using BCI2000 platform and doing EEG experiments with human subjects. In the end, the proposed algorithms to help IAT system detect SSVEP faster are Regression method and Kalman Filter.

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You can send email to saptocondro@ieee.org for more information and also the pdf files of my master project report and my master thesis.

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The scientific paper mentioning me as an author

Title: BCI Demographics: How many (and what kinds of) people can use an SSVEP BCI?

author: B. Allison, I. Volosyak, T. Lüth, D. Valbuena, I. Sugiarto, M.A. Spiegel, A. Teymourian, I.S. Condro (That's me!), A. Brindusescu, K. Stenzel, H. Cecotti & A. Gräser.

Proc. 4th International Brain-Computer Interface Workshop and Training Course.

date: September 18-21, 2008

where: Graz, Austria

pages: 333-338

The scientific paper mentioning me in the acknowledgement

Title: BCI Demographics: How many (and what kinds of) people can use an SSVEP BCI?

author: B. Allison, T. Lüth, D. Valbuena, A. Teymourian, I. Volosyak & A. Gräser

journal: IEEE Transaction on Neural Systems and Rehabilitation Engineering

date: April 2010

volume: 18

number: 2

pages: 107-116

ISSN:1534-4320

The link to this paper can be found here.

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I hope someday I can be an author in IEEE Transactions, especially the first author.

Improvement of Response Times in SSVEP-based Brain-Computer Interface

Starting on December 10th, 2009, I have a master thesis. The thesis should be submitted on May 27th, 2010. The presentation will be conducted in June (I hope).

The title of thesis is "Improvement of Response Times in SSVEP-based Brain-Computer Interface".

The supervisors are

• Prof. Dr.-Ing Axel Gräser
• Dr.-Ing. Ivan Volosyak
• Thorsten Lüth, Dipl.-Ing

The thesis is conducted in the Institute of Automation (IAT) at the University of Bremen.

The research group is no longer called BrainRobot. The name is now BRAIN, which stands for Brain-computer interfaces with Rapid Automated Interfaces for Nonexperts.

Yes, it is funded by European Union. We want to keep up with all research groups in the USA (and Canada) and in the Asia Pasific (China, Japan, Korea, etc).

Back to my thesis!

The proposed question behind the thesis is whether we can improve response times of our system in detecting SSVEP patterns from a subject. We can say that I want to make Bremen BCI system (a little bit) faster than before. I am using time-series manipulation algorithm to do so.

More details will be told in other blog posts.

BrainRobot in CeBit 2008

In March 2008, BrainRobot research group of the IAT of the University of Bremen went to the CeBit in Hannover. We conducted a study of SSVEP-based BCI application there. We were doing experiments whether people can spell words using their brain wave: EEG. We got 106 subjects.

Below is the video about what happened in CeBit.

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• Control software with brainwave patterns
• |
• ZDNet UK

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The result of the experiments can be seen in Allison, et al, 2008, "BCI Demographics: How many (and what kinds of) people can use an SSVEP BCI?", Proc 4th International Brain-computer Interface Workshop and Training Course, Graz, Austria, pp 333-338.

The first neuron

Hello, world!

This is my blog about Brain and I just made the first writing to introduce my blog.

I am Ignatius Sapto Condro Atmawan Bisawarna. People call me "Condro". I participate in the brain research in Bremen since 2008 (or maybe end of 2007). I am a master student in the University of Bremen. There, we have an institute called IAT and a research group called BrainRobot.

End of 2007, I helped a friend putting EEG cap and gel on the head. My friend is Indar Sugiarto. He was doing his project about stimulator for SSVEP using monitor of a desktop PC and a laptop. I think it is the beginning of my participation in the Bremen brain research.

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EEG is Electroencephalogram or Electroencephalography.
SSVEP is Steady-state visually evoked potential.

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In March 2008, BrainRobot and I went to CeBit Hannover. In a week, we got more than 100 subjects participating in SSVEP-based BCI research. We have spelling application and the subjects should spell some words using their EEG.

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BCI is Brain-Computer Interface.

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In November 2008, I started my master project "Final Preparation of the CeBit Data". In 2009, I finished the project and started fixing thesis topic in this area. Now, I have made up my mind and the topic is "Improvement of Response Times of SSVEP-based Brain-Computer Interface". I will do some computing related to Time Series Analysis.

While doing thesis, I made these blog and hoping the AdSense can give me money.