The coordination of EEG rhythms between brain areas can be detected by using Coherence analysis. Is a method developed on the base of classic coherence analysis and signals joint time-frequency representations in recent years. It was used to extract transient characteristics of interactions among brain areas. Describes the temporal, spatial and frequency relationships of brain activities. In this...

## How to extract brain wave bands: Gamma, Beta, Alpha, Theta, Delta

All human beings display five different types of electrical patterns or brain waves over the cortex in order of highest frequency to lowest are as follows: Gamma, Beta, Alpha, Theta, and Delta. Each brain wave has a purpose and helps serve us in optimal mental functioning. If one of the five types of brain waves are either overproduced or under-produced in our brain, it can cause problems [1]...

## Fast Kalman Filter in Matlab

Kalman filtering-smoothing is a fundamental tool in statistical time series analysis: it implements the optimal Bayesian filter in the linear-Gaussian setting, and serves as a key step in the inference algorithms for a wide variety of nonlinear and non-Gaussian models. However, using this kind of filter in small embedded systems is not a good choice due to the computational intensive maths. For...

## How to localize EEG-signals according to the international 10-20 system of electrodes position

In order to perform measurements for feature extraction, it is needed to localize the channels from the data-set recordings to, which contain the raw brain waves with some technical specification of each signal. CHB-MIT Scalp EEG Database is one of the most cited resources used in prediction detection experiments. It is also one of the few publicly available invasive EEG data-sets. The database...

## Edge detection with a given direction using Matlab

The aim of this article is to detect the edges with a given direction in an image. To that end create a function [ E ] = oriented_edges( I, thr, a, da ) that takes as input a double grayscale image Ι, a threshold value thr, a direction a, and an angle da. The output of the function is a binary image Ε where the pixels that meet the following requirements should have the value 1: The pixel...

## Principal Component Analysis using Matlab

PCA is a way of identifying patterns in data, and expressing the data in such a way as to highlight their similarities and differences. Below are the steps of the algorithm: close all; % clear all; clc; % data = load('Data/eeg.mat'); % data = data.data{1,2}; Step 1 – Initialize the dataset, 6 vectors of 32 sample data % % Step 1 - Initialize the dataset, 6 vectors of 32 sample data % X =...