engleski

EEG data processing in neurofeedback

EEG signals are the signatures of neural activities [1]. They are captured by multiple-electrode EEG machines either from inside the brain, over the cortex under the skull, or certain locations over the scalp, and can be recorded in different formats. The signals are normally presented in the time domain, but many new EEG machines are capable of applying simple signal processing tools such as the Fourier transform to perform frequency analysis and equipped with some imaging tools to visualize EEG topographies (maps of the brain activities in the spatial domain) [1]. Neurofeedback (NFB), also called neurotherapyor neurobiofeedback, is a type of biofeedback that uses real-time displays of brain activity—most commonly electroencephalography (EEG), to teach self-regulation of brain function. Typically, sensors are placed on the scalp to measure activity, with measurements displayed using video displays or sound. Neurofeedback can be used to cure the disorder but also to improve athletes’ performance. In this paper, I have extracted the statistical features from observed EEG signal such as mean, standard deviation and gradients. Also I calculated the relative power of the signal and based on all of this features I will make neurofeedback protocol.

EEG, neurofeedback, data processing

nije evidentirano