Apparatus and method for motor imagery classification using eeg
AssigneeKorea University Research and Business Foundation
InventorsDong-Joo KIM, Seho LEE
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Abstract
The present disclosure relates to an apparatus and method for motor imagery classification using electroencephalography (EEG), and more particularly, to an apparatus and method for motor imagery classification that extracts features in different domains included in EEG signals generated during motor imagery in real time and classifies a user's intentions using the features.
Claims11
A motor imagery classification apparatus using electroencephalography (EEG) for predicting a user's intention by analyzing EEG signals generated during motor imagery in chronological order, comprising:
- an information storage unit (110) to collect EEG signals measured by an EEG measurement device and store the EEG signals;
- a feature mapping unit (120) to classify the EEG signals into signals measured for each set unit time, combine features measured at a same unit time among features of the EEG signals arranged in chronological order and arrange the features in a matrix structure;
- a spatial feature analysis unit (130) to set a matrix including the features as each layer to analyze spatial features for each layer;
- a temporal feature analysis unit (140) to analyze changes in the spatial features between the layers arranged in chronological order;
- an intention classification unit (150) to classify motor imagery of the measured EEG signals based on input of values of the spatial features changing for each unit time;
- and
- a feature point generation reading unit (160) to determine if the EEG signals are generated by motor imagery by analyzing signal changes in a specific frequency band included in the EEG signals.
A motor imagery classification method using electroencephalography (EEG) for predicting a user's intention by analyzing EEG signals generated during motor imagery in chronological order, comprising:
- a motor imagery determination step (S110a) of determining, by a feature point generation reading unit (160), if the EEG signals are generated by motor imagery by analyzing signal changes in a specific frequency band included in the EEG signals;
- an information storage step (S110) of collecting the EEG signals measured by an EEG measurement device and storing the EEG signals in an information storage unit (110);
- a block mapping step (S120) of classifying, by a feature mapping unit (120), the EEG signals into signals measured for each set unit time, combining features measured at a same unit time among features of the EEG signals arranged in chronological order and arranging the features in a matrix structure;
- a spatial domain analysis step (S130) of setting, by a spatial feature analysis unit (130), a matrix including the features as each layer to analyze spatial features for each layer;
- a temporal domain analysis step (S140) of analyzing, by a temporal feature analysis unit (140), changes in the spatial features between the layers arranged in chronological order;
- and
- a user's intention classification step (S150) of classifying, by an intention classification unit (150), the motor imagery of the measured EEG signals based on input of values of the spatial features changing for each unit time.
Dependencies are inferred from the claim text.