Common spatial pattern-based feature extraction from the best time segment of BCI data

Comparison Between Different Methods of Feature Extraction in BCI Systems Based on SSVEP

‎There are different feature extraction methods in brain-computer interfaces (BCI) based on Steady-State Visually Evoked Potentials (SSVEP) systems‎. ‎This paper presents a comparison of five methods for stimulation frequency detection in SSVEP-based BCI systems‎. ‎The techniques are based on Power Spectrum Density Analysis (PSDA)‎, ‎Fast Fourier Transform (FFT)‎, ‎Hilbert‎- ‎Huang Transform (H...

Common Spatial Patterns Feature Extraction and Support Vector Machine Classification for Motor Imagery with the SecondBrain

Recently, a large set of electroencephalography (EEG) data is being generated by several high-quality labs worldwide and is free to be used by all researchers in the world. On the other hand, many neuroscience researchers need these data to study different neural disorders for better diagnosis and evaluating the treatment. However, some format adaptation and pre-processing are necessary before ...

Feature eXtraction from sparse time series data

We present a computational methodology for qualitative analysis of sparse and noisy time series. Information about the changes of the signal level within a time series and the number of distinguishable signal levels is extracted and condensed into a pattern string. The qualitative analysis of a time series can be done at several levels of detail to generate pattern strings that encode the seque...

Feature Extraction from Visual Data Feature Extraction from Visual Data

A review on EEG based brain computer interface systems feature extraction methods

The brain – computer interface (BCI) provides a communicational channel between human and machine. Most of these systems are based on brain activities. Brain Computer-Interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. The success of this methodology depends on the selection of methods to process the brain signals in each pha...