SmileToPhone: A Mobile Phone System for Quadriplegic Users Controlled by EEG Signals

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.

Authors and Affiliations

Heyfa Ammar, Mounira Taileb

Keywords

Related Articles

An Architectural Decision Tool Based on Scenarios and Non-functional Requirements

Software architecture design is often based on architects intuition and previous experience. Little methodological support is available, but there are still no effective solutions to guide the architectural design. The m...

Crowdsensing: Socio-Technical Challenges and Opportunities

With the advancement in mobile technology, the sensing and computational capability of mobile devices is increasing. The sensors in mobile devices are being used in a variety of ways to sense and actuate. Mobile crowdsen...

Iris Recognition Using Modified Fuzzy Hypersphere Neural Network with different Distance Measures

In this paper we describe Iris recognition using Modified Fuzzy Hypersphere Neural Network (MFHSNN) with its learning algorithm, which is an extension of Fuzzy Hypersphere Neural Network (FHSNN) proposed by Kulkarni et...

Modified Farmland Fertility Optimization Algorithm for Optimal Design of a Grid-connected Hybrid Renewable Energy System with Fuel Cell Storage: Case Study of Ataka, Egypt

In this paper, a Modified Farmland Fertility Optimization algorithm (MFFA) has been presented for optimal sizing of a grid connected hybrid system including photovoltaic (PV), wind turbines and fuel cell (FC). The system...

Ethernet Based Remote Monitoring And Control Of Temperature By Using Rabbit Processor

Networking is a major component of the processes and control instrumentation systems as the network’s architecture solves many of the Industrial automation problems. There is a great deal of benefits in the process of in...

Download PDF file
  • EP ID EP259147
  • DOI 10.14569/IJACSA.2017.080566
  • Views 70
  • Downloads 0

How To Cite

Heyfa Ammar, Mounira Taileb (2017). SmileToPhone: A Mobile Phone System for Quadriplegic Users Controlled by EEG Signals. International Journal of Advanced Computer Science & Applications, 8(5), 537-541. https://europub.co.uk/articles/-A-259147