PERFORMANCE OF BIOMEDICAL SIGNALS WITH FFT ANALYSIS

Biomedical signal processing has taken place in recent days to extract information needed to track the disease and to detect new biology. EEG impulses in particular reflect the brain's working mechanism, and can be used for a broad variety of purposes, e.g. BCI. The biggest downside of this application is the low efficiency of EEG signal capture. When the EEG signal is registered, noise produced has a highly susceptible effect on the efficiency of Neural Signals and BCI applications. In addition, extraction of noise characteristics is known to be a significant element in the treatment of biomedical signals. This paper therefore uses the Power Spectral Density (PSD) model to establish the potential features and identify the distinction between the coherency signal and the inconsistency signal. PSD is used for the extraction of noise and for the study of coordination by the Fourier coherence analysis process. The results demonstrate that the approach suggested improves brain coordination by using a coherent analysis from Fourier.