Statistical analysis of electroencephalographic data in human applications
Electroencephalogram (EEG), Statistical Analysis, Visually Evoked Static Potentials (SSVEP), P300.
The motor activities of the human body, as well as those related to decision making and emotional and psychic issues, can be understood through the analysis of electrical signals from the brain, also known as electroencephalogram (EEG) signals. The study and application of electroencephalographic data has been growing within the scientific community. It is known that the use of these signals forms the basis of the development of the Computer Brain Interface (ICC), and that these represent the future of assistive technologies, especially those aimed at people who do not have motor control. However, the extraction of characteristics and patterns of these signals is still a complex process. Surveys involving ICC and EEG signals usually implement event related potentials (ERP) analyzes; being the main ones: the static potentials evoked visually (SSVEP) and the potential P300. In general, they are responses to external stimuli (visual, auditory, tactile), and are widely used to recognize patterns in EEG signals associated with changes in brain activity. The purpose of this paper is to analyze the signs of the neural activity of individuals who are exposed to external stimuli using the identification of potential SSVEP and P300. The project uses a low-cost, non-invasive EEG signal sensor with wireless, wireless technology. It is expected to extract EEG data to the point of making possible the correlation of these with characteristics that can be applied in control tools.