Implementation of an Embedded Web Server Application for Wireless Control of Brain Computer Interface Based Home Environments

Brain Computer Interface (BCI) based environment control systems could facilitate life of people with neuromuscular diseases, reduces dependence on their caregivers, and improves their quality of life. As well as easy usage, low-cost, and robust system performance, mobility is an important functionality expected from a practical BCI system in real life. In this study, in order to enhance users' mobility, we propose internet based wireless communication between BCI system and home environment. We designed and implemented a prototype of an embedded low-cost, low power, easy to use web server which is employed in internet based wireless control of a BCI based home environment. The embedded web server provides remote access to the environmental control module through BCI and web interfaces. While the proposed system offers to BCI users enhanced mobility, it also provides remote control of the home environment by caregivers as well as the individuals in initial stages of neuromuscular disease. The input of BCI system is P300 potentials. We used Region Based Paradigm (RBP) as stimulus interface. Performance of the BCI system is evaluated on data recorded from 8 non-disabled subjects. The experimental results indicate that the proposed web server enables internet based wireless control of electrical home appliances successfully through BCIs.

[1]  J.D. Bayliss,et al.  Use of the evoked potential P3 component for control in a virtual apartment , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[2]  Yoshikazu Nakajima,et al.  A Two-Level Predictive Event-Related Potential-Based Brain–Computer Interface , 2013, IEEE Transactions on Biomedical Engineering.

[3]  Eda Akman Aydin,et al.  Region based Brain Computer Interface for a home control application , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[4]  G. Pfurtscheller,et al.  Conversion of EEG activity into cursor movement by a brain-computer interface (BCI) , 2004, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[5]  Wanli Min,et al.  Distance-Constrained Orthogonal Latin Squares for Brain-Computer Interface , 2012, Journal of Medical Systems.

[6]  Chin-Teng Lin,et al.  Brain Computer Interface-Based Smart Living Environmental Auto-Adjustment Control System in UPnP Home Networking , 2014, IEEE Systems Journal.

[7]  Peter Willett,et al.  What is a tutorial , 2013 .

[8]  Dean J Krusienski,et al.  A comparison of classification techniques for the P300 Speller , 2006, Journal of neural engineering.

[9]  Xiaorong Gao,et al.  A BCI-based environmental controller for the motion-disabled , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[10]  Yijun Wang,et al.  Visual and Auditory Brain–Computer Interfaces , 2014, IEEE Transactions on Biomedical Engineering.

[11]  F Babiloni,et al.  P300-based brain–computer interface for environmental control: an asynchronous approach , 2011, Journal of neural engineering.

[12]  Alain Rakotomamonjy,et al.  BCI Competition III: Dataset II- Ensemble of SVMs for BCI P300 Speller , 2008, IEEE Transactions on Biomedical Engineering.

[13]  Eloisa Vargiu,et al.  Brain Computer Interface on Track to Home , 2015, TheScientificWorldJournal.

[14]  Reza Fazel-Rezai,et al.  A Review of Hybrid Brain-Computer Interface Systems , 2013, Adv. Hum. Comput. Interact..

[15]  M. Slater,et al.  Control of a Smart Home with a Brain-Computer Interface , 2008 .

[16]  Byoung-Kyong Min,et al.  Neuroimaging-based approaches in the brain-computer interface. , 2010, Trends in biotechnology.

[17]  Rebeca Corralejo,et al.  A P300-based brain–computer interface aimed at operating electronic devices at home for severely disabled people , 2014, Medical & Biological Engineering & Computing.

[18]  Eda Akman Aydin,et al.  Classification of P300 event related potentials with Discrete Wavelet Transform , 2015, 2015 23nd Signal Processing and Communications Applications Conference (SIU).

[19]  Francisco Sepulveda,et al.  Wavelets and ensemble of FLDs for P300 classification , 2009, 2009 4th International IEEE/EMBS Conference on Neural Engineering.

[20]  J. Polich Updating P300: An integrative theory of P3a and P3b , 2007, Clinical Neurophysiology.

[21]  Kiseon Kim,et al.  Review of Wireless Brain-Computer Interface Systems , 2013 .

[22]  J. Wolpaw,et al.  Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects , 2009, IEEE Reviews in Biomedical Engineering.

[23]  Gernot R. Müller-Putz,et al.  Control of an Electrical Prosthesis With an SSVEP-Based BCI , 2008, IEEE Transactions on Biomedical Engineering.

[24]  E. Donchin,et al.  Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. , 1988, Electroencephalography and clinical neurophysiology.

[25]  Mel Slater,et al.  Using a P300 Brain Computer Interface for Smart Home Control , 2009 .

[26]  M Congedo,et al.  A review of classification algorithms for EEG-based brain–computer interfaces , 2007, Journal of neural engineering.

[27]  Febo Cincotti,et al.  Smart homes to improve the quality of life for all , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[28]  G. Oriolo,et al.  Non-invasive brain–computer interface system: Towards its application as assistive technology , 2008, Brain Research Bulletin.

[29]  Mel Slater,et al.  Virtual Smart Home Controlled by Thoughts , 2009, 2009 18th IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises.

[30]  Febo Cincotti,et al.  Advanced brain computer interface for communication and control , 2010, AVI.

[31]  Mel Slater,et al.  Brain Computer Interface for Virtual Reality Control , 2009, ESANN.

[32]  Reza Fazel-Rezai,et al.  A region-based P300 speller for brain-computer interface , 2009, Canadian Journal of Electrical and Computer Engineering.

[33]  Cuntai Guan,et al.  High performance P300 speller for brain-computer interface , 2004, IEEE International Workshop on Biomedical Circuits and Systems, 2004..

[34]  Febo Cincotti,et al.  Asynchronous P300-Based Brain-Computer Interface to Control a Virtual Environment: Initial Tests on End Users , 2011, Clinical EEG and neuroscience.

[35]  Mohammad Hassan Moradi,et al.  A new approach for EEG feature extraction in P300-based lie detection , 2009, Comput. Methods Programs Biomed..

[36]  G. Pfurtscheller,et al.  Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.

[37]  Luca Mainardi,et al.  Performance measurement for brain–computer or brain–machine interfaces: a tutorial , 2014, Journal of neural engineering.

[38]  G. Pfurtscheller,et al.  An SSVEP BCI to Control a Hand Orthosis for Persons With Tetraplegia , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[39]  Marco Aiello,et al.  International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises , 2009 .

[40]  Christian Laugier,et al.  Controlling a Wheelchair Indoors Using Thought , 2007, IEEE Intelligent Systems.

[41]  Michael Bensch,et al.  Design and Implementation of a P300-Based Brain-Computer Interface for Controlling an Internet Browser , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.