A review of classification algorithms for EEG-based brain–computer interfaces
نویسندگان
چکیده
منابع مشابه
TOPICAL REVIEW A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces
In this paper we review classification algorithms used to design BrainComputer Interface (BCI) systems based on ElectroEncephaloGraphy (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI. PACS...
متن کاملA Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update.
OBJECTIVE Most current Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) are based on machine learning algorithms. There is a large diversity of classifier types that are used in this field, as described in our 2007 review paper. Now, approximately 10 years after this review publication, many new algorithms have been developed and tested to classify EEG signals in BCIs. ...
متن کاملA review of classification algorithms for EEG-based brain–computer interfaces
In this paper we review classification algorithms used to design BrainComputer Interface (BCI) systems based on ElectroEncephaloGraphy (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI. PACS...
متن کاملClassification of EEG-based motor imagery BCI by using ECOC
AbstractAccuracy in identifying the subjects’ intentions for moving their different limbs from EEG signals is regarded as an important factor in the studies related to BCI. In fact, the complexity of motor-imagination and low amount of signal-to-noise ratio for EEG signal makes this identification as a difficult task. In order to overcome these complexities, many techniques such as variou...
متن کاملClassification of EEG Signals for Discrimination of Two Imagined Words
In this study, a Brain-Computer Interface (BCI) in Silent-Talk application was implemented. The goal was an electroencephalograph (EEG) classifier for three different classes including two imagined words (Man and Red) and the silence. During the experiment, subjects were requested to silently repeat one of the two words or do nothing in a pre-selected random order. EEG signals were recorded by ...
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ژورنال
عنوان ژورنال: Journal of Neural Engineering
سال: 2007
ISSN: 1741-2560,1741-2552
DOI: 10.1088/1741-2560/4/2/r01