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Conference Paper: Study on EEG-based mouse system by using brain-computer interface

TitleStudy on EEG-based mouse system by using brain-computer interface
Authors
KeywordsBrain-Computer Interface
Eeg-Based Mouse
Feature Extraction
Imagination Of Hand Movements
Malanobis Distance Classifier
Issue Date2009
Citation
The 2009 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurements Systems (VECIMS 2009), Hong Kong, China, 11-13 May 2009. In Conference Proceedings, 2009, p. 236-239 How to Cite?
AbstractThis paper aimed to design an EEG-based mouse system by using brain-computer interface (BCI) to move a cursor on a computer display.This system to provide an alternative communication or control channel for patients with severe motor disabilities. Such patients might become able to select target on a computer monitor by moving a cursor through mental activity.The user could move the cursor just through imaging his/her hand operation on mouse without any actual action while the movement direction that he/she wanted to choose was lighted in the cue line of four-direction choice circulation. This system used an adaptive algorithm to recognize cursor control patterns in multichannel EEG frequency spectra. The algorithm included preprocessing, feature extraction, and classification. A Fisher ratio was defined to determine the characteristic frequency band. The spectral powering this band was calculated as feature parameter to distinguish the task state of imagination of hand movements (IHM) from free state of non-IHM. Mahalanobis distance classifier was employed to recognize the effective task pattern and produce the trigger signal as cursor controller. Relevant experiment results showed that this system achieved 80% accuracy for IHM task/free pattern classification. This EEG-based mouse system is feasible to drive the cursor's four-direction movement and may provide a new communication and control option for patients with severe motor disabilities. ©2009 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/173412
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorMing, Den_US
dc.contributor.authorZhu, Yen_US
dc.contributor.authorQi, Hen_US
dc.contributor.authorWan, Ben_US
dc.contributor.authorHu, Yen_US
dc.contributor.authorLuk, KDKen_US
dc.date.accessioned2012-10-30T06:30:55Z-
dc.date.available2012-10-30T06:30:55Z-
dc.date.issued2009en_US
dc.identifier.citationThe 2009 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurements Systems (VECIMS 2009), Hong Kong, China, 11-13 May 2009. In Conference Proceedings, 2009, p. 236-239en_US
dc.identifier.urihttp://hdl.handle.net/10722/173412-
dc.description.abstractThis paper aimed to design an EEG-based mouse system by using brain-computer interface (BCI) to move a cursor on a computer display.This system to provide an alternative communication or control channel for patients with severe motor disabilities. Such patients might become able to select target on a computer monitor by moving a cursor through mental activity.The user could move the cursor just through imaging his/her hand operation on mouse without any actual action while the movement direction that he/she wanted to choose was lighted in the cue line of four-direction choice circulation. This system used an adaptive algorithm to recognize cursor control patterns in multichannel EEG frequency spectra. The algorithm included preprocessing, feature extraction, and classification. A Fisher ratio was defined to determine the characteristic frequency band. The spectral powering this band was calculated as feature parameter to distinguish the task state of imagination of hand movements (IHM) from free state of non-IHM. Mahalanobis distance classifier was employed to recognize the effective task pattern and produce the trigger signal as cursor controller. Relevant experiment results showed that this system achieved 80% accuracy for IHM task/free pattern classification. This EEG-based mouse system is feasible to drive the cursor's four-direction movement and may provide a new communication and control option for patients with severe motor disabilities. ©2009 IEEE.en_US
dc.languageengen_US
dc.relation.ispartofProceedings of the IEEE-VECIMS 2009en_US
dc.subjectBrain-Computer Interfaceen_US
dc.subjectEeg-Based Mouseen_US
dc.subjectFeature Extractionen_US
dc.subjectImagination Of Hand Movementsen_US
dc.subjectMalanobis Distance Classifieren_US
dc.titleStudy on EEG-based mouse system by using brain-computer interfaceen_US
dc.typeConference_Paperen_US
dc.identifier.emailHu, Y:yhud@hku.hken_US
dc.identifier.emailLuk, KDK:hcm21000@hku.hken_US
dc.identifier.authorityHu, Y=rp00432en_US
dc.identifier.authorityLuk, KDK=rp00333en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/VECIMS.2009.5068900en_US
dc.identifier.scopuseid_2-s2.0-70349933141en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70349933141&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage236en_US
dc.identifier.epage239en_US
dc.identifier.isiWOS:000270760700046-
dc.identifier.scopusauthoridMing, D=9745824400en_US
dc.identifier.scopusauthoridZhu, Y=24722062200en_US
dc.identifier.scopusauthoridQi, H=7202348852en_US
dc.identifier.scopusauthoridWan, B=7102316798en_US
dc.identifier.scopusauthoridHu, Y=7407116091en_US
dc.identifier.scopusauthoridLuk, KDK=7201921573en_US
dc.customcontrol.immutablesml 170512 amended-

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