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The self-paced graz brain-computer interface: methods and applications.

Scherer R, Schloegl A, Lee F, Bischof H, Jansa J, Pfurtscheller G - Comput Intell Neurosci (2007)

Bottom Line: The presented system is able to automatically reduce electrooculogram (EOG) artifacts, to detect electromyographic (EMG) activity, and uses only three bipolar EEG channels.Two applications are presented: the freeSpace virtual environment (VE) and the Brainloop interface.The Brainloop interface provides an interface between the Graz-BCI and Google Earth.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Brain-Computer Interfaces, Institute for Knowledge Discovery, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria. reinhold.scherer@tugraz.at

ABSTRACT
We present the self-paced 3-class Graz brain-computer interface (BCI) which is based on the detection of sensorimotor electroencephalogram (EEG) rhythms induced by motor imagery. Self-paced operation means that the BCI is able to determine whether the ongoing brain activity is intended as control signal (intentional control) or not (non-control state). The presented system is able to automatically reduce electrooculogram (EOG) artifacts, to detect electromyographic (EMG) activity, and uses only three bipolar EEG channels. Two applications are presented: the freeSpace virtual environment (VE) and the Brainloop interface. The freeSpace is a computer-game-like application where subjects have to navigate through the environment and collect coins by autonomously selecting navigation commands. Three subjects participated in these feedback experiments and each learned to navigate through the VE and collect coins. Two out of the three succeeded in collecting all three coins. The Brainloop interface provides an interface between the Graz-BCI and Google Earth.

No MeSH data available.


(a) Protocol used for the collection of EEG and EOGsamples to set up the EMG detection and EOG reduction. The recording wasdivided into several segments, each separated by a 5-s resting period.Instructions were presented on a computer screen. At the beginning and end ofeach task low -and high-warning tones were presented, respectively. (b)Positions of EOG electrodes (reference left mastoid, ground right mastoid). Thethree EOG electrodes are placed above the nasion, and below the outer canthi ofthe eyes, generating in a right-angled triangle. The legs of the triangle formtwo spatially orthogonal components (modified from [18]).
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fig1: (a) Protocol used for the collection of EEG and EOGsamples to set up the EMG detection and EOG reduction. The recording wasdivided into several segments, each separated by a 5-s resting period.Instructions were presented on a computer screen. At the beginning and end ofeach task low -and high-warning tones were presented, respectively. (b)Positions of EOG electrodes (reference left mastoid, ground right mastoid). Thethree EOG electrodes are placed above the nasion, and below the outer canthi ofthe eyes, generating in a right-angled triangle. The legs of the triangle formtwo spatially orthogonal components (modified from [18]).

Mentions: At the beginning of each BCI session, a 2-minutesegment of artifact free EEG was recorded in order to estimate theAR-parameters ai (model order p = 10) by using theBurg method. See Figure 1(a) for details on the protocol used to collect theartifact free EEG. Subjects were instructed to sit relaxed and not move.


The self-paced graz brain-computer interface: methods and applications.

Scherer R, Schloegl A, Lee F, Bischof H, Jansa J, Pfurtscheller G - Comput Intell Neurosci (2007)

(a) Protocol used for the collection of EEG and EOGsamples to set up the EMG detection and EOG reduction. The recording wasdivided into several segments, each separated by a 5-s resting period.Instructions were presented on a computer screen. At the beginning and end ofeach task low -and high-warning tones were presented, respectively. (b)Positions of EOG electrodes (reference left mastoid, ground right mastoid). Thethree EOG electrodes are placed above the nasion, and below the outer canthi ofthe eyes, generating in a right-angled triangle. The legs of the triangle formtwo spatially orthogonal components (modified from [18]).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2266812&req=5

fig1: (a) Protocol used for the collection of EEG and EOGsamples to set up the EMG detection and EOG reduction. The recording wasdivided into several segments, each separated by a 5-s resting period.Instructions were presented on a computer screen. At the beginning and end ofeach task low -and high-warning tones were presented, respectively. (b)Positions of EOG electrodes (reference left mastoid, ground right mastoid). Thethree EOG electrodes are placed above the nasion, and below the outer canthi ofthe eyes, generating in a right-angled triangle. The legs of the triangle formtwo spatially orthogonal components (modified from [18]).
Mentions: At the beginning of each BCI session, a 2-minutesegment of artifact free EEG was recorded in order to estimate theAR-parameters ai (model order p = 10) by using theBurg method. See Figure 1(a) for details on the protocol used to collect theartifact free EEG. Subjects were instructed to sit relaxed and not move.

Bottom Line: The presented system is able to automatically reduce electrooculogram (EOG) artifacts, to detect electromyographic (EMG) activity, and uses only three bipolar EEG channels.Two applications are presented: the freeSpace virtual environment (VE) and the Brainloop interface.The Brainloop interface provides an interface between the Graz-BCI and Google Earth.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Brain-Computer Interfaces, Institute for Knowledge Discovery, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria. reinhold.scherer@tugraz.at

ABSTRACT
We present the self-paced 3-class Graz brain-computer interface (BCI) which is based on the detection of sensorimotor electroencephalogram (EEG) rhythms induced by motor imagery. Self-paced operation means that the BCI is able to determine whether the ongoing brain activity is intended as control signal (intentional control) or not (non-control state). The presented system is able to automatically reduce electrooculogram (EOG) artifacts, to detect electromyographic (EMG) activity, and uses only three bipolar EEG channels. Two applications are presented: the freeSpace virtual environment (VE) and the Brainloop interface. The freeSpace is a computer-game-like application where subjects have to navigate through the environment and collect coins by autonomously selecting navigation commands. Three subjects participated in these feedback experiments and each learned to navigate through the VE and collect coins. Two out of the three succeeded in collecting all three coins. The Brainloop interface provides an interface between the Graz-BCI and Google Earth.

No MeSH data available.