>
Fa   |   Ar   |   En
   Discriminative Common Spatial Pattern Sub‑bands Weighting Based on Distinction Sensitive Learning Vector Quantization Method in Motor Imagery Based Brain‑computer Interface  
   
نویسنده Jamaloo Fatemeh ,Mikaeili Mohammad
منبع journal of medical signals and sensors - 2015 - دوره : 5 - شماره : 3 - صفحه:156 -161
چکیده    Common spatial pattern (csp) is a method commonly used to enhance the effects of event‑related desynchronization and event‑related synchronization present in multichannel electroencephalogram‑based brain‑computer interface (bci) systems. in the present study, a novel csp sub‑band feature selection has been proposed based on the discriminative information of the features. besides, a distinction sensitive learning vector quantization based weighting of the selected features has been considered. finally, after the classification of the weighted features using a support vector machine classifier, the performance of the suggested method has been compared with the existing methods based on frequency band selection, on the same bci competitions datasets. the results show that the proposed method yields superior results on “ay” subject dataset compared against existing approaches such as sub‑band csp, filter bank csp (fbcsp), discriminative fbcsp, and sliding window discriminative csp.
کلیدواژه Brain-computer Interfaces ,computer-assisted ,electroencephalography ,learning ,signal processing ,support vector machines
آدرس shahed university, Department of Engineering, ایران, shahed university, Department of Engineering, ایران
 
     
   
Authors
  
 
 

Copyright 2023
Islamic World Science Citation Center
All Rights Reserved