From Thinking To Text –Alphabet Recognition Through Brainwaves

Abstract

Our brain is made up of billions of brain cells called neurons, which use electricity to communicate with each other. The combination of millions of neurons sending signals at once produces an enormous amount of electrical activity in the brain, which can be detected using sensitive medical equipment (such as an EEG), measuring electricity levels over areas of the scalp. The combination of electrical activity of the brain is commonly called a Brainwave pattern, because of its cyclic, 'wave-like' nature. Our mind regulates its activities by means of electric waves which are registered in the brain, emitting tiny electrochemical impulses of varied frequencies, which can be registered by an electroencephalogram. Paralysis patients are those which loss or impairment of voluntary movement in a body part, caused by injury or disease of the nerves, brain, or spinal cord. Due to this disease they are not able to communicate with other people. To make them able to communicate we have developed this application. Now the patient wears the EEG headset, the EEG headset send the application the values of different types of brain waves and on the basis of these values our application will guess about the alphabet which the patient was thinking. This program will be developed using Java. The program will use Artificial Neural Networks for machine learning. The target population of our project is patient with paralysis, and the also anyone can use this application for their own ease. The scope of work is limited to getting brain waves values via EEG headset and the decision support structure will be based upon it.Through this achieved recognition of alphabets, this project can serve to become a basis for further development to speech recognition which will serve the paralyzed and otherwise completely handicapped people to convey their inner most thoughts.