Preprocessing of EEG for imagery movement based on integration of multi-domain

Autor:	Yu Ji, Ji-zhong Shen, Pan Wang, Jin-he Shi
Rok vydání:	2012
Předmět:	medicine.diagnostic_test business.industry Computer science Interface (computing) Feature extraction Wavelet transform Pattern recognition Electroencephalography Statistical classification ComputingMethodologies_PATTERNRECOGNITION medicine Preprocessor Artificial intelligence business
Zdroj:	FSKD
DOI:	10.1109/fskd.2012.6233913
Popis:	In previous EEG preprocessing algorithms of brain-computer interface, there are problems such as huge amounts of processing EEG data and the ignorance of EEG's variance from person to person. This paper has proposed a novel method of preprocessing algorithm based on integration of multi-domain, using Fisher distance to select the sampling electrodes and spatial preprocessing is added to the traditional algorithm which is just based on time-frequency domain. It is proved to be effective and practical in overcoming the above drawbacks with experiments of EEG collection. The experiment results show that the proposed method can reduce more than 96.9% of the total processing EEG data and decrease 95.8% of the BCI system's total running time while remain almost equal classification accuracy, contributes to the online application.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a576aeca250c4fe23e6dd48dac862c22 https://doi.org/10.1109/fskd.2012.6233913 Zobrazit plný text záznamu