Correlation-based common spatial pattern (CCSP): A novel extension of CSP for classification of motor imagery signal
نویسندگان
چکیده
منابع مشابه
Common Spatial Patterns Feature Extraction and Support Vector Machine Classification for Motor Imagery with the SecondBrain
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 ...
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 کاملLocal Temporal Correlation Common Spatial Patterns for Single Trial EEG Classification during Motor Imagery
Common spatial pattern (CSP) is one of the most popular and effective feature extraction methods for motor imagery-based brain-computer interface (BCI), but the inherent drawback of CSP is that the estimation of the covariance matrices is sensitive to noise. In this work, local temporal correlation (LTC) information was introduced to further improve the covariance matrices estimation (LTCCSP). ...
متن کاملClassification of Right/Left Hand Motor Imagery by Effective Connectivity Based on Transfer Entropy in EEG Signal
The right and left hand Motor Imagery (MI) analysis based on the electroencephalogram (EEG) signal can directly link the central nervous system to a computer or a device. This study aims to identify a set of robust and nonlinear effective brain connectivity features quantified by transfer entropy (TE) to characterize the relationship between brain regions from EEG signals and create a hierarchi...
متن کاملA novel method for motor imagery EEG adaptive classification based biomimetic pattern recognition
The real on-line BCI is indeed a hotspot at present whose performance however is limited by the problems of non-stationary etc. In this paper, a novel method for the adaptive classification of motor imagery EEG data based Biomimetic Pattern Recognition (BPR) through introducing three adaptive operators is proposed. Considering that the large amounts of labeled samples are difficult to get in th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLOS ONE
سال: 2021
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0248511