Autosoft Journal

Online Manuscript Access

Analysis of Collaborative Brain Computer Interface (BCI) based personalized GUI for differently abled



Brain-Computer Interfaces (BCI) use Electroencephalography (EEG) signals recorded from the brain scalp, which enable a communication between the human and the outside world. The present study helps the patients who are people locked-in to manage their needs such as accessing of web url’s, sending/receiving sms to/from mobile device, personalized music player, personalized movie player, wheelchair control and home appliances control. In the proposed system, the user needs are designed as a button in the form of a matrix, in which the main panel of rows and columns button is flashed in 3 sec intervals. Subjects were asked to choose the desired task/need from the main panel of the GUI by blinking their eyes twice. The double eye blink signals extracted by using the bio-sensor of NeuroSky’s mind wave device with portable EEG sensors are used as the command signal. Each task is designed and implemented using a Matlab tool. The developed Personalized GUI application collaborated with the EEG device accesses the user’s need. Once the system identifies the desired option through the input control signal, the appropriate algorithm is called and performed. The users can also locate the next required option within the matrix. Therefore, users can easily navigate through the GUI Model. A list of personalized music, movies, books and web URL’s are preloaded in the database. Hence, it could be suitable to assist disabled people to improve their quality of life. Analysis of variance (ANOVA) is also carried out to find out the significant signals influencing a user’s need in order to improve the motion characteristics of the brain computer interface based system.



Total Pages: 11
Pages: 747-757


Manuscript ViewPdf Subscription required to access this document

Obtain access this manuscript in one of the following ways

Already subscribed?

Need information on obtaining a subscription? Personal and institutional subscriptions are available.

Already an author? Have access via email address?


Volume: 24
Issue: 4
Year: 2018

Cite this document


Bacivarov, Ioana, Mircea Ionita, and Peter Corcoran. "Statistical Models of Appearance for Eye Tracking and Eye-Blink Detection and Measurement." IEEE Transactions on Consumer Electronics 54.3 (2008): 1312-1320. Crossref. Web.

Bastos-Filho, Teodiano Freire et al. "Towards a New Modality-Independent Interface for a Robotic Wheelchair." IEEE Transactions on Neural Systems and Rehabilitation Engineering 22.3 (2014): 567-584. Crossref. Web.

Boord, Peter et al. "Discrimination of Left and Right Leg Motor Imagery for Brain-computer Interfaces." Medical & Biological Engineering & Computing 48.4 (2010): 343-350. Crossref. Web.

Cecotti H. IEEE

Gandhi, Vaibhav et al. "EEG-Based Mobile Robot Control Through an Adaptive Brain-Robot Interface." IEEE Transactions on Systems, Man, and Cybernetics: Systems 44.9 (2014): 1278-1285. Crossref. Web.

Gentiletti, G.G. et al. "Command of a Simulated Wheelchair on a Virtual Environment Using a Brain-Computer Interface." IRBM 30.5-6 (2009): 218-225. Crossref. Web.

Jin, Jing et al. "Optimized Stimulus Presentation Patterns for an Event-Related Potential EEG-Based Brain-computer Interface." Medical & Biological Engineering & Computing 49.2 (2010): 181-191. Crossref. Web.

Karjalainen, P.A. et al. "Subspace Regularization Method for the Single-Trial Estimation of Evoked Potentials." IEEE Transactions on Biomedical Engineering 46.7 (1999): 849-860. Crossref. Web.

Khushaba, R N et al. "Driver Drowsiness Classification Using Fuzzy Wavelet-Packet-Based Feature-Extraction Algorithm." IEEE Transactions on Biomedical Engineering 58.1 (2011): 121-131. Crossref. Web.

Lenhardt, A., M. Kaper, and H.J. Ritter. "An Adaptive P300-Based Online Brain-Computer Interface." IEEE Transactions on Neural Systems and Rehabilitation Engineering 16.2 (2008): 121-130. Crossref. Web.

Long J. Biomedical Engineering

Lugger, K. et al. "Feature Extraction for on-Line EEG Classification Using Principal Components and Linear Discriminants." Medical & Biological Engineering & Computing 36.3 (1998): 309-314. Crossref. Web.

Mahmoudi, Babak, and Abbas Erfanian. "Electro-Encephalogram Based Brain-computer Interface: Improved Performance by Mental Practice and Concentration Skills." Medical & Biological Engineering & Computing 44.11 (2006): 959-969. Crossref. Web.

Postelnicu C. Biomedical Engineering

Sammaiah A. ICETECT

Tanaka, K., K. Matsunaga, and H.O. Wang. "Electroencephalogram-Based Control of an Electric Wheelchair." IEEE Transactions on Robotics 21.4 (2005): 762-766. Crossref. Web.

Throckmorton, C. S. et al. "Bayesian Approach to Dynamically Controlling Data Collection in P300 Spellers." IEEE Transactions on Neural Systems and Rehabilitation Engineering 21.3 (2013): 508-517. Crossref. Web.

Yom-Tov, E., and G. F. Inbar. "Detection of Movement-Related Potentials from the Electro-Encephalogram for Possible Use in a Brain-Computer Interface." Medical & Biological Engineering & Computing 41.1 (2003): 85-93. Crossref. Web.


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present


TSI Press
18015 Bullis Hill
San Antonio, TX 78258 USA
PH: 210 479 1022
FAX: 210 479 1048