DocumentCode :
718213
Title :
EarEEG based visual P300 Brain-Computer Interface
Author :
Farooq, Faisal ; Looney, David ; Mandic, Danilo P. ; Kidmose, Preben
Author_Institution :
Dept. of Eng., Aarhus Univ., Aarhus, Denmark
fYear :
2015
fDate :
22-24 April 2015
Firstpage :
98
Lastpage :
101
Abstract :
The translation of non-invasive Brain-Computer Interfaces (BCI) from the only possible communication pathway for paralyzed patients into more widespread applications is limited by: the lack of effective, user-friendly and robust paradigms, low information transfer rates (ITR), and lack of suitable electroencephalography (EEG) recording platforms. This study addresses the last point by exploring the extent to which the recently introduced EarEEG technology, which provides an unobtrusive, discreet and user-friendly way of recording EEG, can be used in BCI applications. This was approached by comparing conventional on-scalp EEG and EarEEG recordings in a well-established visual P300 BCI setup. The two recording methods were compared qualitatively by comparing Event-Related Potential (ERP) waveforms, and quantitatively in terms of P300 signal-to-noise ratios (SNR) and ITRs of the BCI paradigm. The study showed similar ERP waveforms and on par P300 SNRs from both on-scalp and ear electrodes, and only a 6.5% decrease in single channel ITR for ear electrodes compared to on-scalp electrodes. This demonstrates that the EarEEG platform is a feasible technology for P300-based BCIs.
Keywords :
biomedical communication; brain-computer interfaces; electroencephalography; BCI applications; BCI paradigm; ERP waveforms; EarEEG technology; EarEEG-based visual P300 brain-computer interface; P300 signal-to-noise ratios; P300-based BCI; electroencephalography recording platforms; event-related potential waveforms; low-information transfer rates; noninvasive brain-computer interfaces; Conferences; Ear; Electrodes; Electroencephalography; Scalp; Signal to noise ratio; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on
Conference_Location :
Montpellier
Type :
conf
DOI :
10.1109/NER.2015.7146569
Filename :
7146569
Link To Document :
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