Design of Low-Power EEG-Based Brain–Computer Interface

The idea of communication through thoughts developed into reality with the growth of computer and communication technologies and the understanding of how a human brain works. One of the main benefactors of this technology and the prime reasons for development of BCI or brain–computer interface is the physically challenged section of the society which will be able to carry on with their regular activities with ease in the near future with the help of ongoing research works in BCI which are primarily focused in the area of neuroprosthetics to restore the damaged hearing, movement and sight in the patients. In this paper, a low-power brain–computer interface design is suggested. The main motive of this paper was to check whether a cost-efficient BCI system can be implemented using basic components and discuss the possible applications where such low-range devices can be of use.

[1]  N. Miller,et al.  Learning motivated by electrical stimulation of the brain. , 1954, The American journal of physiology.

[2]  J J Vidal,et al.  Toward direct brain-computer communication. , 1973, Annual review of biophysics and bioengineering.

[3]  Suat Karakaya,et al.  Design and Implementation of a Multi Sensor Based Brain Computer Interface for a Robotic Wheelchair , 2017, J. Intell. Robotic Syst..

[4]  Suhrud M. Rajguru,et al.  The Cochlear Implant: Historical Aspects and Future Prospects , 2012, Anatomical record.

[5]  Bernhard Schölkopf,et al.  Methods Towards Invasive Human Brain Computer Interfaces , 2004, NIPS.

[6]  M M Haglund,et al.  Low-grade gliomas associated with intractable epilepsy: seizure outcome utilizing electrocorticography during tumor resection. , 1993, Journal of neurosurgery.

[7]  Naoaki Tanaka,et al.  Clinical applications of magnetoencephalography , 2009, Human brain mapping.

[8]  Jonathan R Wolpaw,et al.  Guest Editorial The Third International Meeting on Brain-Computer Interface Technology: Making a Difference , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[9]  M.M. Moore,et al.  Real-world applications for brain-computer interface technology , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[10]  S. Rihana,et al.  Portable EEG recording system for BCI application , 2016, 2016 3rd Middle East Conference on Biomedical Engineering (MECBME).

[11]  Naveed Iqbal Rao,et al.  Towards a Brain Computer Interface using wavelet transform with averaged and time segmented adapted wavelets , 2009, 2009 2nd International Conference on Computer, Control and Communication.

[12]  R. Ilmoniemi,et al.  Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain , 1993 .

[13]  Jyh-Yeong Chang,et al.  Novel Dry Polymer Foam Electrodes for Long-Term EEG Measurement , 2011, IEEE Transactions on Biomedical Engineering.

[14]  Yusuf Abdullahi Badamasi.  The working principle of an Arduino , 2014, 2014 11th International Conference on Electronics, Computer and Computation (ICECCO).

[15]  N. Crone,et al.  High-frequency gamma oscillations and human brain mapping with electrocorticography. , 2006, Progress in brain research.

[16]  D.J. McFarland,et al.  The wadsworth BCI research and development program: at home with BCI , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[17]  Hans Berger,et al.  Über das Elektrenkephalogramm des Menschen , 1931, Archiv für Psychiatrie und Nervenkrankheiten.

[18]  Vivek Prabhakaran,et al.  A review of the progression and future implications of brain-computer interface therapies for restoration of distal upper extremity motor function after stroke , 2016, Expert review of medical devices.