A Novel Paradigm for Multiple Target Selection Using a two class Brain Computer Interface

V. Gandhi, G Prasad, D Coyle, Laxmidhar Behera, TM McGinnity

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A brain computer interface (BCI) allows a person to communicate with external devices using electroencephalogram (EEG) or other brain signals. A typical BCI scheme consists of data acquisition, feature extraction and classification. Using the classifier output, a control command is issued to the intended devices and the subject is provided appropriate feedback. As a part of feedback, a graphical user interface (GUI) plays a very important role as a front end display for the BCI user and enhancing overall communication bandwidth. This paper focuses on the interface design aspect of a BCI so as to provide effective control of a wheelchair or robot arm application. A motor imagery prediction based paradigm is used to create a semi synchronous interface with a focus on presentation of a new task for selection as well as to optimally utilize the subject intentions. From a theoretical assessment, it is expected that the overall time required to select from six choices using the proposed GUI will be much less compared to existing designs. Also, being a 2 class paradigm, it is expected that the probability of error occurrence is minimized along with a quicker traverse between choices and this may allow a limited bandwidth BCI to operate an external device with multiple degree of freedom and choose from multiple different choices efficiently and effectively.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages6
Publication statusPublished - 2009
Event2009 Irish Signals and Systems Conference - Dublin
Duration: 1 Jan 2009 → …

Conference

Conference2009 Irish Signals and Systems Conference
Period1/01/09 → …

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Brain computer interface
Graphical user interfaces
Feedback
Bandwidth
Wheelchairs
Electroencephalography
Feature extraction
Data acquisition
Brain
Classifiers
Display devices
Robots
Communication

Cite this

@inproceedings{3fdfcd1f68744190a090ca46a0430f00,
title = "A Novel Paradigm for Multiple Target Selection Using a two class Brain Computer Interface",
abstract = "A brain computer interface (BCI) allows a person to communicate with external devices using electroencephalogram (EEG) or other brain signals. A typical BCI scheme consists of data acquisition, feature extraction and classification. Using the classifier output, a control command is issued to the intended devices and the subject is provided appropriate feedback. As a part of feedback, a graphical user interface (GUI) plays a very important role as a front end display for the BCI user and enhancing overall communication bandwidth. This paper focuses on the interface design aspect of a BCI so as to provide effective control of a wheelchair or robot arm application. A motor imagery prediction based paradigm is used to create a semi synchronous interface with a focus on presentation of a new task for selection as well as to optimally utilize the subject intentions. From a theoretical assessment, it is expected that the overall time required to select from six choices using the proposed GUI will be much less compared to existing designs. Also, being a 2 class paradigm, it is expected that the probability of error occurrence is minimized along with a quicker traverse between choices and this may allow a limited bandwidth BCI to operate an external device with multiple degree of freedom and choose from multiple different choices efficiently and effectively.",
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booktitle = "Unknown Host Publication",

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Gandhi, V, Prasad, G, Coyle, D, Behera, L & McGinnity, TM 2009, A Novel Paradigm for Multiple Target Selection Using a two class Brain Computer Interface. in Unknown Host Publication. 2009 Irish Signals and Systems Conference, 1/01/09.

A Novel Paradigm for Multiple Target Selection Using a two class Brain Computer Interface. / Gandhi, V.; Prasad, G; Coyle, D; Behera, Laxmidhar; McGinnity, TM.

Unknown Host Publication. 2009.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - A brain computer interface (BCI) allows a person to communicate with external devices using electroencephalogram (EEG) or other brain signals. A typical BCI scheme consists of data acquisition, feature extraction and classification. Using the classifier output, a control command is issued to the intended devices and the subject is provided appropriate feedback. As a part of feedback, a graphical user interface (GUI) plays a very important role as a front end display for the BCI user and enhancing overall communication bandwidth. This paper focuses on the interface design aspect of a BCI so as to provide effective control of a wheelchair or robot arm application. A motor imagery prediction based paradigm is used to create a semi synchronous interface with a focus on presentation of a new task for selection as well as to optimally utilize the subject intentions. From a theoretical assessment, it is expected that the overall time required to select from six choices using the proposed GUI will be much less compared to existing designs. Also, being a 2 class paradigm, it is expected that the probability of error occurrence is minimized along with a quicker traverse between choices and this may allow a limited bandwidth BCI to operate an external device with multiple degree of freedom and choose from multiple different choices efficiently and effectively.

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