To enhance the performance of electroencephalography (EEG)-based emotional HCI, this paper proposes an improved common spatial pattern combined with a channel-selection strategy (ICSPCS) for EEG-based emotion recognition. Specifically, we first use a common spatial pattern algorithm to design a ...
[2] Keng A K , Yang C Z , Chuanchu W , et al. Filter Bank Common Spatial Pattern Algorithm on BCI Competition IV Datasets 2a and 2b[J]. Frontiers in Neuroscience, 2012, 6:39. [3] Ramoser H , Muller-Gerking J . Optimal spatial filtering of single trial EEG during imagined hand...
Common spatial pattern (CSP) is a mathematical procedure used in signal processing for separating a multivariate signal into additive subcomponents which have maximum differences in variance between two windows. This algorithm is mainly used in motor imagery based BCI for processing EEG data. ...
This type of algorithm is called the time-frequency common spatial pattern. CSP is basically a two-class feature extraction algorithm and is not designed for multiclass mode. Ref. [32] is a study that has generalized this tool from two-class to multiclass. The method of generalization of ...
We provide a non-greedy iterative algorithm to maximize the objective function of CSP-L21. Experiments on a toy example and three popular data sets of BCI competitions illustrate that the proposed method can efficiently extract discriminative features....
Implementing Common Spatial Pattern (CSP) algorithm for MI-BCI from scratch with python brain-computer-interfacecommon-spatial-pattern UpdatedOct 24, 2020 Jupyter Notebook sajjadkarimi91/motor-imagery-BCI Star6 A MATLAB toolbox for classification of motor imagery tasks in EEG-based BCI system with ...
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How to improve the classification accuracy is a key issue in four-class motor imagery-based brain-computer interface (MI-BCI) systems. In this paper, a method based on phase synchronization analysis and common spatial pattern (CSP) algorithm is proposed. The proposed method embodies the idea of...
A Modified Common Spatial Pattern Algorithm Customized for Feature Dimensionality Reduction in fNIRS-Based BCIs. Functional near-infrared spectroscopy (fNIRS) is a non-invasive multi-channel imaging tool for assessing brain activities, which has shown its high potential in brain-computer interface (BCI)...
Common Spatial Pattern (SP) algorithm has been proved to be effective in Brain Computer Interface (BCI) for extracting features from Electroencephalogram (EEG) signals used in motor imagery tasks, but it is vulnerable to noise and the problem of over-fitting. Many algorithms have been devised to...