Spatial Filtering Optimisation in Motor Imagery Eeg-based Bci

اسناد مشابه

• Automatic selection of the number of spatial filters for motor-imagery BCI

  سند علمی۲۰۱۲ESANNYuan Yang, Sylvain Chevallier, Joe Wiart, Isabelle Bloch

  Common spatial pattern (CSP) is widely used for constructing spatial filters to extract features for motor-imagery-based BCI. One main parameter in CSP-based classification is the number of spatial filters used. An automatic method relying on Rayleigh quotient is presented to est

• Discriminative Learning of Propagation and Spatial Pattern for Motor Imagery EEG Analysis

  سند علمی۲۰۱۳Neural computationXinyang Li, Haihong Zhang, Cuntai Guan, Sim Heng Ong

  Effective learning and recovery of relevant source brain activity patterns is a major challenge to brain-computer interface using scalp EEG. Various spatial filtering solutions have been developed. Most current methods estimate an instantaneous demixing with the assumption of unc

• Notice of Removal: Removal of ocular artifacts using ICA and adaptive filter for motor imagery-based BCI

  مقاله‌ی دسترسی آزاد۲۰۲۳IEEE/CAA Journal of Automatica Sinica['Chung-Song Kim', 'Jinwei Sun', 'Dan Liu', 'Sung Wook Paek', '']

  Removed.

• Robust Spatial Filters on Three-Class Motor Imagery EEG Data Using Independent Component Analysis

  سند علمی۲۰۱۴Bangyan Zhou, Xiaopei Wu, Lei Zhang, Zhao Lv

  Independent Component Analysis (ICA) was often used to separate movement related independent components (MRICs) from Electroencephalogram (EEG) data. However, to obtain robust spatial filters, complex characteristic features, which were manually selected in most cases, have been

• Subject-specific time-frequency selection for multi-class motor imagery-based BCIs using few Laplacian EEG channels

  سند علمی۲۰۱۷Biomed. Signal Proc. and ControlYuan Yang, Sylvain Chevallier, Joe Wiart, Isabelle Bloch

  The essential task of a motor imagery brain–computer interface (BCI) is to extract the motor imageryrelated features from electroencephalogram (EEG) signals for classifying motor intentions. However, the optimal frequency band and time segment for extracting such features differ

• Non-homogeneous spatial filter optimization for ElectroEncephaloGram (EEG)-based motor imagery classification

  سند علمی۲۰۱۳NeurocomputingTae-Eui Kam, Heung-Il Suk, Seong-Whan Lee

  Neuronal power attenuation or enhancement in specific frequency bands over the sensorimotor cortex, called Event-Related Desynchronization (ERD) or Event-Related Synchronization (ERS), respectively, is a major phenomenon in brain activities involved in imaginary movement of body