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Intelligent System for Neurological Disorder by EEG Signal Analysis Using Artificial Neural Network

Author

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  • M.K. Bhaskar
  • Surendra
  • Bohra

Abstract

The Life of people is becoming complicated every day due to explosion of population leading to crises of land, employment, agricultural proceeds, price hikes etc. This is followed by crunch of resources on the one hand and drastic fall in per capita income of country man also educational improvement is followed by its fruitlessness except intellectual development, under this situation countryman is facing stress on mind. Also the insecurity of careers and mental tensions are growing exponentially in the life of people. This may take the youth either to the direction of becoming criminal or to direction of surrendering before the uncontrollable pressure of helplessness. Both the paths give rise to further insecurity and mental tensions. The ultimate part which is attacked is mental health of person due to overstressed conditions. It is therefore recovery of mental health has become an important challenging concern of the doctors. The human brain produces electrical signals which prove vital in understanding the degree of abnormality that may, in many cases, result in a person behaving unusually. The information contained in these signals is recorded via an EEG machine, which is able to extract even the most subtle details from the electrical waves that the brain signals generate usually, the signals from the aforementioned device are interpreted by the specialists who specialize in this very thing but heir defection is susceptible to errors which prove fatal in some cases. This research presents an autonomous system, capable of detecting the occurrence of an brain disorder, without the help of an expert.

Suggested Citation

  • M.K. Bhaskar & Surendra & Bohra, 2016. "Intelligent System for Neurological Disorder by EEG Signal Analysis Using Artificial Neural Network," International Journal of Scientific Research in Science, Engineering and Technology, International Journal of Scientific Research in Science, Engineering and Technology, vol. 2(6), pages 122-127, December.
  • Handle: RePEc:ijs:ijsrse:v2:y2016:i6:id:hijsrset162644
    Note: Article URL: https://ijsrset.com/IJSRSET162644
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