Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI
نویسندگان
چکیده
منابع مشابه
Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI
Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern filter (CSP) as preprocessing step before feature extraction and classification. The CSP method is a supervised algorithm and therefore needs subject-specific training data for calibration, which is very time consuming to collect. In order to reduce the amount of calibration data that is needed for a ne...
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Recently, a large set of electroencephalography (EEG) data is being generated by several high-quality labs worldwide and is free to be used by all researchers in the world. On the other hand, many neuroscience researchers need these data to study different neural disorders for better diagnosis and evaluating the treatment. However, some format adaptation and pre-processing are necessary before ...
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Common spatial pattern (CSP) is becoming a standard way to combine linearly multi-channel EEG data in order to increase discrimination between two motor imagery tasks. We demonstrate in this article that the use of robust estimates allows improving the quality of CSP decomposition and CSP-based BCI. Furthermore, a scheme for electrode subset selection is proposed. It is shown that CSP with such...
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One source of EEG data quality deterioration is noise. The others are artifacts, such as the eye blinking, oculogyration, heart beat, or muscle activity. All these factors mentioned above contribute to the disappointing and poor quality of EEG signals. There are some solutions which allow increase of this signals quality. One of them is Common Spatial Patterns. Some scientific papers report tha...
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ژورنال
عنوان ژورنال: Computational Intelligence and Neuroscience
سال: 2011
ISSN: 1687-5265,1687-5273
DOI: 10.1155/2011/217987