Abstract: Quadriplegic people are unable to use mobile devices without the aid of other persons which can be devastating for them both socially and economically. This has motivated many researchers to propose hardware and software solutions that operate as intermediates between the impaired users and their devices: accessibility switches, joysticks and head movements. However, the efficiency of these tools is limited in some conditions. To alleviate this problem, we propose to exploit electroencephalographic signals captured via an adequate headset. More precisely, the user is asked to perform a facial expression that will be recognized by the system through the analysis of the EEG signals. Several facial expressions are offered and each one corresponds to a command wirelessly sent to the mobile device and executed. This Brain Computer Interface based system is called SmileToPhone. It enables the quadriplegic patients to use their smartphones in an easy way with a minimum of effort and with respect to studied Human-Computer-Interaction requirements. The system includes the main functionalities of a smartphone such as making calls and sending messages. The evaluation of the system usability showed that most of the time, users were able to use the different functionalities of the system in an easy way. The current results are encouraging and motivating to add more features to the system.

Heyfa Ammar and Mounira Taileb, “SmileToPhone: A Mobile Phone System for Quadriplegic Users Controlled by EEG Signals” International Journal of Advanced Computer Science and Applications(IJACSA), 8(5), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080566

@article{Ammar2017,
title = {SmileToPhone: A Mobile Phone System for Quadriplegic Users Controlled by EEG Signals},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080566},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080566},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {5},
author = {Heyfa Ammar and Mounira Taileb}
}