Biofeedback EEG data integration and visualization analytics for endurance exercise practices: Data integration and visualization analytics of biofeedback EEG

Automatic processing of the data in order to determine the status of work and identification of the activity and brain-wave frequencies becomes necessary for the modern systems in the in the diagnosis of biofeedback among athletes. Electroencephalography frequency of brain waves are registered with use of several or even a dozen sensors mounted on a machine with a BTS-Stal Sys-Italy device. However, the sensors can register “noise” values, and therefore we present a different approach based on known techniques of computer science and statistics which allowed us to increase the sensitivity by improving detection performance. Statistic methods allowed an identification of data anomalies, such as extreme, outliers and missing values. Combining information with soft computing tool can distinct the level of electrical activity of the analyzed brain-wave frequencies. Visualization analytics and regression method are impressive solution for maintaining high measurement accuracy indicates the effectiveness of this method in optimization of psychophysiological processes among athletes.