Brain status recognition using FPGA)

  • Dr. Jayashree Vaddin
  • Akhilesh Kelkar
  • Rohini Hedavu
  • Apoorva Pise
Keywords: Brain waves, NeuroSky Headset, FPGA, signal processing, MATLAB, EEG, psycho physiological

Abstract

Human brain, the most complex and confusing
control system controls the entire human body and its activities just
by sending electric impulses to relevant body parts. While doing
that, it processes data such as sensory information,
awareness, thinking etc. The six brainwaves viz.; Infrared, Delta,
Theta, Alpha, Beta, & Gamma are generated by brain are in the range
of 0.5 Hz to 30 Hz. The main objective of this proposed project
is to acquire and process the human brain waves. Filtering
and amplifying of brain signals are big issues while processing
brain waves, since the brain signals have very low amplitude and
are in the low frequency. We aim to identify the brain state such as
awake, normal alert consciousness, physically and mentally relaxed,
awake but drowsy, deep (dreamless) sleep, loss of bodily awareness,
reduced consciousness, deep meditation, dreams, light sleep, REM
sleep, heightened perception etc in real time. To carry out real time
processing of digital signals and to maximize the efficiency,
processing on a powerful signal processor viz., FPGA is selected.
It supports programming for a specific task without hardware restrictions besides being faster than its embedded counterparts which are not powerful enough for
real time processing. So in this paper, we propose a system for
the brain wave capturing, filtering and classification using
artificial intelligence in MATLAB IDE. The developed program
will be converted to HDL using HDL coder of MATLAB and
then it would be dumped in FPGA for testing the functionality of
proposed system.

References

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[3] Marco Paleari, RyadChellali, “Feature of Multimodel
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1674-5/08, IEEE 2010. 4-5/08,IEEE
2010.
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[4] Literature review about Brainwave Test,
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Published
2019-04-11
How to Cite
Vaddin, D. J., Kelkar, A., Hedavu, R., & Pise, A. (2019). Brain status recognition using FPGA). Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146. Retrieved from https://asianssr.org/index.php/ajct/article/view/720
Section
Article

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