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Limited By:	Subject = BCI;

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Displaying Results 1 - 5 of 5 on page 1 of 1

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An analysis of EEG signals present during target search (2012)

Healy, Graham

An analysis of EEG signals present during target search (2012)

Healy, Graham

Abstract:

Recent proof-of-concept research has appeared highlighting the applicability of using Brain Computer Interface (BCI) technology to utilise a subjects visual system to classify images. This technique involves classifying a users EEG (Electroencephalography) signals as they view images presented on a screen. The premise is that images (targets) that arouse a subjects attention generate distinct brain responses, and these brain responses can then be used to label the images. Research thus far in this domain has focused on examining the tasks and paradigms that can be used to elicit these neurologically informative signals from images, and the correlates of human perception that modulate them. While success has been shown in detecting these responses in high speed presentation paradigms, there is still an open question as to what search tasks can ultimately benefit from using an EEG based BCI system. In this thesis we explore: (1) the neural signals present during visual search tasks th...

http://doras.dcu.ie/16778/

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An investigation of triggering approaches for the rapid serial visual presentation paradigm in brain computer interfacing (2016)

Wang, Zhengwei; Healy, Graham; Smeaton, Alan F.; Ward, Tomás E.

An investigation of triggering approaches for the rapid serial visual presentation paradigm in brain computer interfacing (2016)

Wang, Zhengwei; Healy, Graham; Smeaton, Alan F.; Ward, Tomás E.

Abstract:

The rapid serial visual presentation (RSVP) paradigm is a method that can be used to extend the P300 based brain computer interface (BCI) approach to enable high throughput target image recognition applications. The method requires high temporal resolution and hence, generating reliable and accurate stimulus triggers is critical for high performance execution. The traditional RSVP paradigm is normally deployed on two computers where software triggers generated at runtime by the image presentation software on a presentation computer are acquired along with the raw electroencephalography (EEG) signals by a dedicated data acquisition system connected to a second computer. It is often assumed that the stimulus pre- sentation timing as acquired via events arising in the stimulus presentation code is an accurate reflection of the physical stimulus presentation. This is not necessarily the case due to various and variable latencies that may arise in the overall system. This paper describes...

http://doras.dcu.ie/21265/

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Optimising the number of channels in EEG-augmented image search (2011)

Healy, Graham; Smeaton, Alan F.

Optimising the number of channels in EEG-augmented image search (2011)

Healy, Graham; Smeaton, Alan F.

Abstract:

Recent proof-of-concept research has appeared showing the applicability of Brain Computer Interface (BCI) technology in combination with the human visual system, to classify images. The basic premise here is that images that arouse a participant’s attention generate a detectable response in their brainwaves, measurable using an electroencephalograph (EEG). When a participant is given a target class of images to search for, each image belonging to that target class presented within a stream of images should elicit a distinctly detectable neural response. Previous work in this domain has primarily focused on validating the technique on proof of concept image sets that demonstrate desired properties and on examining the capabilities of the technique at various image presentation speeds. In this paper we expand on this by examining the capability of the technique when using a reduced number of channels in the EEG, and its impact on the detection accuracy.

http://doras.dcu.ie/16387/

Marked Mark

Single-trial detection in EEG and MEG: Keeping it linear (2003)

Parra, Lucas C.; Alvino, Chris; Tang, Akaysha; Pearlmutter, Barak A.; Yeung, Nick; Osma...

Single-trial detection in EEG and MEG: Keeping it linear (2003)

Parra, Lucas C.; Alvino, Chris; Tang, Akaysha; Pearlmutter, Barak A.; Yeung, Nick; Osman, Allen; Sajda, Paul

Abstract:

Conventional electroencephalography (EEG) and magnetoencephalography (MEG) analysis often rely on averaging over multiple trials to extract statistically relevant di7erences between two or more experimental conditions. We demonstrate that by linearly integrating information over multiple spatially distributed sensors within a prede9ned time window, one can discriminate conditions on a trial-by-trial basis with high accuracy. We restrict ourselves to a linear integration as it allows the computation of a spatial distribution of the discriminating source activity. In the present set of experiments the resulting source activity distributions correspond to functional neuroanatomy consistent with the task (e.g. contralateral sensory-motor cortex and anterior cingulate).

http://mural.maynoothuniversity.ie/5538/

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The Berlin Brain-Computer Interface presents the novel mental typewriter Hex-o-Spell. (2006)

Blankertz, Benjamin; Dornhege, Guido; Krauledat, Matthias; Schröder, Michael; Williamso...

The Berlin Brain-Computer Interface presents the novel mental typewriter Hex-o-Spell. (2006)

Blankertz, Benjamin; Dornhege, Guido; Krauledat, Matthias; Schröder, Michael; Williamson, John; Murray-Smith, Roderick; Müller, Klaus-Robert

Abstract:

We present a novel typewriter application ‘Hex-o-Spell’ that is specifically tailored to the characteristics of direct brain-to-computer interaction. The high bandwidth at which a user may perceive information from the display is used in an appealing visualization based on hexagons. On the other hand the control of the application is possible at low bandwidth using only two control commands (mental states) and is relatively stable against delays and the like. The effectiveness and robustness of the interface was demonstrated at the CeBIT 2006 (world’s largest IT fair) where two subjects operated the mental typewriter at a speed of up to 7.6 char/min. It was developed within the Berlin Brain- Computer Interface project in cooperation with specialists for Human Computer Interaction.

http://mural.maynoothuniversity.ie/1786/

Displaying Results 1 - 5 of 5 on page 1 of 1