References

Some books, papers, URLS, etc.
  1. [1] Adam Fendelman, What is T9 Predictive Text? May 2017. Retrieved from: http://cellphones.about.com/od/phoneglossary/g/t9predictivetext.htm
  2. [2] B. Rebsamen, E. Burdet, Q. Zeng, H. Zhang, M. Ang, C. L. Teo, C. Guan, and C. Laugier. Hybrid P300 and mu-beta brain computer interface to operate a brain controlled wheelchair. In Proceedings of the 2nd International Convention on Re-habilitation Engineering & Assistive Technology, 2008, pp.51-55.
  3. [3] BrainMaster Technologies, Nearest EEG. Retrieved from: http://www.brainm.com/software/pubs/dg/BA_10-20_ROI_Talairach/nearesteeg.htm
    4. [4] D. Hood, D. Joseph, A. Rakotonirainy, S. Sridharan, and C. Fookes. Use of brain computer interface to drive: preliminary results. In Proceedings of the 4th Interna-tional Conference on Automotive User Interfaces and Interactive Vehicular Applica-tions, 2012, pp.103-106.
  4. [5] David Paul A. Clio and the Economics of QWERTY. The American economic re-view 75.2, 1985, pp.332-337.
  5. [6] Emotiv EEG Headset Comparison Chart. Retrieved from: https://www.emotiv.com/comparison/
  6. [7] Emotiv Official User Forum: “Mental Commands – How does it Work?”, 2016. Retrieved from: https://www.emotiv.com/forums/topic/Mental_Commands___How_does_it_Work_/
  7. [8] Hiran Ekanayake, P300 and Emotiv EPOC: Does Emotiv EPOC capture real EEG, 2010. Retrieved from: http://neurofeedback.visaduma.info/emotivresearch.htm
  8. [9] Kevin Curran, Derek Woods, and Barry O. Riordan. Investigating text input meth-ods for mobile phones. Telematics and Informatics 23.1, 2006, pp.1-21.
  9. [10] Klára Fiedlerová. Possibilities of Text Input for Handicapped People. Master’s the-sis, Czech Technical University in Prague, Czech Republic, 2012.
  10. [11] K. Mohanchandra, S. Saha,G.M. Lingaraju, Chapter 10 EEG Based Brain Com-puter Interface for Speech Communication: Principles and Applications, Springer International Publishing Switzerland 2015, pp.273-293.
  11. [12] Mark C. Detweiler, Robert M. Schumacher Jr, and Nicholas L. Gattuso Jr. Alpha-betic input on a telephone keypad. Proceedings of the Human Factors Society An-nual Meeting. Vol. 34. No. 3. Sage CA: Los Angeles, CA: SAGE Publications, 1990.
  12. [13] Mark F. Bear, Barry W. Connors, Michael A. Paradiso. Neuroscience - Exploring the Brain, Third Edition, Lippincott Williams & Wilkins Press, 2007.
  13. [14] M. M. Fouad et al., Chapter 1 Brain Computer Interface: A Review, Brain-Computer Interfaces, Springer International Publishing Switzerland 2015, pp.4-18.
  14. [15] R. A. Ramadan et al., Chapter 2 Basics of Brain Computer, Brain-Computer Inter-faces, Springer International Publishing Switzerland 2015, pp.40-47.
  15. [16] Rytis Maskeliunas, et al., Consumer-grade EEG devices: are they usable for con-trol tasks? PeerJ 4 (2016): e1746.
  16. [17] O. Robert, F. Pascal, M. Eric, S. Jan-Mathijs. FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. J. Com-put. Intell. Neurosci. 2011, 156869 (2011).
  17. [18] Sayan Sarcar, et al., Virtual keyboard design: State of the arts and research issues. Students' Technology Symposium (TechSym), Proceedings of the 2010 IEEE. IEEE, 2010.
  18. [19] Shuo Qiu, Kyle Rego, Lei Zhang, Feifei Zhong, Micheal Zhong, MotionInput: Gestural Text Entry in the Air, 2013. Retrieved from: http://www.columbia.edu/~sq2144/MotionInput.pdf
  19. [20] S. Lingaratnam, D. Murray, A. Carle, Sue W. Kirsa, R. Paterson, D. Rischin. De-veloping a performance data suite to facilitate lean improvement in a chemotherapy day unit. Oncol. Pract. 9(4), 2013, pp.115–121.
  20. [21] Stanford Course: CS231n: Convolutional Neural Networks for Visual Recognition. Retrieved from: http://cs231n.stanford.edu/
  21. [22] T. Kameswara Rao, M. Rajya Lakshmi, T. V. Prasad. An exploration on brain computer interface and its recent trends. Int. Adv. Res. Artif. Intell. (IJARI) 1(8), 2013, pp.17–22.
  22. [23] V. Bajaj, R. B. Pachori, Chapter 8 Detection of Human Emotions Using Features Based on the Multiwavelet Transform of EEG Signals, Brain-Computer Interfaces, Springer International Publishing Switzerland 2015, pp.215-240.
  23. [24] V. Sudha Rani, Mohammed Ali Shaik. IMPLEMENTATION OF USER FRIEND-LY TEXT MESSAGING. International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 2, Issue 4, July-August 2013, pp.85-92.
  24. [25] Wikipedia, 10-20 System (EEG). Retrieved from: https://en.wikipedia.org/wiki/10%E2%80%9320_system_(EEG)
  25. [26] Wikipedia, E.161. Retrieved from: https://en.wikipedia.org/wiki/E.161
  26. [27] Wikipedia, Electroencephalography. Retrieved from: https://en.wikipedia.org/wiki/Electroencephalography
  27. [28] Wikipedia, Input Method. Retrieved from: https://en.wikipedia.org/wiki/Input_method.
  28. [29] Wikipedia, Lobes of the brain. Retrieved from: https://en.wikipedia.org/wiki/Lobes_of_the_brain
  29. [30] Wikipedia, QWERTY. Retrieved from: https://en.wikipedia.org/wiki/QWERTY
  30. [31] Wikipedia, Trie. Retrieved from: https://en.wikipedia.org/wiki/Trie.
  31. [32] C++ library for Predictive text input (T9). Retrieved from: https://github.com/delkon/pretext
  32. [33] Official Emotiv SDK. Retrieved from: https://github.com/Emotiv/community-sdk/releases
  33. [34] Python T9 Implementation. Retrieved from: https://github.com/npezolano/Python-T9-implementation
  34. [35] Emotiv User Manual for Example C++, Getting Started with Emotiv SDK , EMO-TIV Inc 2016. Retrieved from: https://github.com/Emotiv/community-sdk/blob/master/Getting_started_with_Emotiv_SDK.pdf
  35. EEG: https://en.wikipedia.org/wiki/Electroencephalography
  36. EMOTIV official website: https://www.emotiv.com/