Open Access

ARTICLE

Analysis of Collaborative Brain Computer Interface (BCI) Based Personalized GUI for Differently Abled

M. Uma^a,c, T. Sheela^b

^a R&D Center, Bharathiar University, Coimbatore-641046, India;
^b Department of Information Technology, Sri Sai Ram Engineering College, Chennai, India;
^c Department of Software Engineering, SRM University, Chennai, India

* Corresponding Author: M. Uma,

Intelligent Automation & Soft Computing 2018, 24(4), 747-757. https://doi.org/10.1080/10798587.2017.1332804

Abstract

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.

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Keywords

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