DocumentCode
1799971
Title
Classifications of motor imagery tasks in brain computer interface using Euclidean distance
Author
Fira, Monica ; Aldea, Roxana ; Lazar, Anca ; Goras, Liviu
Author_Institution
Inst. for Comput. Sci., Iasi, Romania
fYear
2014
fDate
25-27 Nov. 2014
Firstpage
121
Lastpage
124
Abstract
In this paper we propose and discuss a new classification method of motor imagery tasks based on patterns and Euclidean distance. The proposed method is simple, fast, but considerably sensitive with respect to the selected features/frequencies for classification. Choosing a predefined number of features leads to results similar to GTEC/BCI2000 while an optimal selection gives improved results but still requires additional investigation.
Keywords
brain-computer interfaces; electroencephalography; medical signal processing; pattern classification; signal classification; EEG signals; Euclidean distance; GTEC/BCI2000; brain computer interface; electroencephalography; motor imagery task classification; Electric potential; Electroencephalography; Euclidean distance; Monitoring; Software; Testing; Training; Brain computer interface; EEG; classifications; movement imagery paradigm;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Network Applications in Electrical Engineering (NEUREL), 2014 12th Symposium on
Conference_Location
Belgrade
Print_ISBN
978-1-4799-5887-0
Type
conf
DOI
10.1109/NEUREL.2014.7011477
Filename
7011477
Link To Document