Motor Imagery-Based Brain-Computer Interface (BCI) System with CSP Algorithm Implementation

In current motor imagery-based Brain-Computer Interface (BCI) systems, the Common Spatial Patterns (CSP) method serves as an effective signal processing technique widely adopted in practice. This program implements the fundamental CSP algorithm featuring signal preprocessing, feature extraction, and classifier training with practical code demonstrations.

MATLAB Implementation of CSP Algorithm for Asynchronous Brain-Computer Interface Feature Extraction

CSP algorithm for asynchronous brain-computer interface feature value extraction. Brain-Computer Interface (BCI) technology provides a non-muscular communication channel enabling direct information exchange between the brain and external environment. BCI converts brain signals into control commands for external devices, bypassing traditional peripheral nerve and muscle pathways [1]. Implementation involves spatial filtering techniques and eigenvalue decomposition using MATLAB's signal processing toolbox.

Basic Common Spatial Pattern (CSP) Algorithm

Basic Common Spatial Pattern Algorithm with Implementation Insights