Monitoring attention level in real time; a web application

Within this thesis that attention level was monitored and measured; EEG measurements were conducted with Emotiv Epoc Headset and data was real- timely saved in database. Saved frequency data was filtered with the method FFT (Fast Fourier Transform) and this filtering method conveyed us to beta, teta, alfa, delta etc. frequency intervals that we wished to obtain. This filter we worked is also inside a small application that is loaded on the computer in the individual's use. The filter the individual has was made to measure real- timely attention level by analyzing data according to scientific norms and at the same time it can define the individual's emotional type and stress level. Moreover, there is also a manager page that we can reach time based frequency data over management panel of web interface of measured frequencies and obtained data. On this page as we can be aware of emotion type and stress level of each participant, it makes us be able to treat to the individual in an emergency case fast.