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- W2885544663 abstract "Brain computer interface (BCI) is one of the technologies growing at an exponential rate with its applications extended to medical and non-medical fields. EEG is widely used in BCI for detection and analysis of abnormalities of the brain. EEG is characterized by inherently high temporal resolution and precision, low spatial resolution and specificity plus contains artifacts and redundant or noise information both from the subject and equipment interferences. Thus, feature extraction is a critical issue in translation algorithm development for BCI. Above all, BCI still faces a lot challenges that results in performance variation across and even within subjects. Thus, this work provides a concise but all encompassing review of methods that have been adopted in the recent time for development of an EEG classification in BCI." @default.
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- W2885544663 date "2018-01-01" @default.
- W2885544663 modified "2023-09-24" @default.
- W2885544663 title "EEG Classification in Brain Computer Interface (BCI): A Pragmatic Appraisal" @default.
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