An EEG analysis approach towards brain-to-brain synchronization

Mind Synchronization is an attempt to make a voiceless communication, without using tongue, indications, or gestures. It is to entertain the medical field in making devices which can help deaf and dumb people to express and deliver their thoughts with their counterparts and an attempt to make a system in which a subject just has to think of a word in his conscious mind and it can be conveyed to the desired destination securely, silently and accurately. When a person initializes his brain to say something, an image of the word or alphabets are portrayed at the back of his mind. This process has been done less than a second that's why no one can notice this through a naked eye, scientifically, it is proved that anything a man thinks or tries to convey is stored in subconscious mind in the form of an image. Every alphabet thought in mind results with the slight change in the Electroencephalogram of the person. This slight change distinguished and used to make this project working. The suggested method investigates the usefulness of Time - Frequency Analysis as a methodology for classifying various alphabets using electroencephalogram (EEG). For signal acquisition the Electrodes are placed on a subject scalp followed by Instrumentation amplifier which consisting of two stage amplifier i.e., (OPAMP INA118 and TL082), optocoupler subject projection circuit has also been designed for the safety of circuit and the subject too, along with these circuitry Right Driven Leg circuit has also designed to reduce Common-mode interference during acquiring the brain EEG signal from a subject. Narrow band multi feedback filter were also designed to just detect the Alpha wave activity of the subject brain because of aim of this project just to detect these waves for this purpose (8 to 13 HZ) narrow band filleter designed at these ranges. TMS320C6713 digital signal processing kit was also used to perform periodogram on the acquired EEG and extracting the local maxima of the input acquired for the further analysis. The results suggest this approach can retrieve alphabets in half a second. Up to the full number of methods can be used for EEG signal detection to differentiate alphabets. Ranges of data for some alphabets are also collected.