P300 electroencephalogram signal detection method and device for data migration, electronic equipment and medium
An EEG signal and EEG technology, applied in the directions of diagnostic recording/measurement, medical science, diagnosis, etc., can solve the problems of small amount of data, abnormal shape of P300 signal, difficult detection, etc., to reduce interference, high total classification and correct rate, the effect of overcoming the presence of anomalies
Active Publication Date: 2022-01-21
ZHEJIANG UNIV
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[0003] The purpose of the embodiment of this application is to provide a P300 EEG signal detection method and device, electronic equipment, and medium for data migration to solve the abnormal shape of P300 signals in epileptic patients , small amount of data, and technical problems that are difficult to detect
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[0044] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.
[0045] The terminology used in this application is for the purpose of describing particular embodiments only, and is not intended to limit the application. As used in this application and the appended claims, the singular forms "a", "the", and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that the term...
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The invention discloses a P300 electroencephalogram signal detection method and device for data migration, electronic equipment and a medium. The method comprises the steps of performing multi-domain preprocessing on a target electroencephalogram signal containing a P300 component and a migration data set; extracting multi-domain features from the target electroencephalogram signal and the migration data set after multi-domain preprocessing; taking the migration data set subjected to multi-domain feature extraction as a training set, taking a target electroencephalogram signal training data set subjected to multi-domain feature extraction as a test set, and using a multi-domain combined classifier based on a confidence coefficient; taking the correctly classified target electroencephalogram signal training data set subjected to multi-domain feature extraction as a pre-trained target electroencephalogram signal training set; and and performing secondary training on a multi-domain combined classifier by using the pre-trained target electroencephalogram signal training set, and classifying a target electroencephalogram signal test data set subjected to multi-domain feature extraction so as to obtain a final target electroencephalogram signal P300 classification result.
Description
technical field [0001] The present application relates to the technical field of EEG signal processing, in particular to a data migration P300 EEG signal detection method and device, electronic equipment, and media. Background technique [0002] The P300 EEG signal is a positive wave peak that occurs about 300 milliseconds after a person receives a "target stimulus" that occurs with a small probability in the routine irrelevant stimulus. It is a very commonly used event-related potential component. In the brain-computer interface The system is often used to control and communicate the EEG signals of external devices. It is also the main object of lie detection research such as hidden information tests, and is also commonly used to evaluate the cognitive function of the subjects. Detecting P300 components in EEG signals and distinguishing the presence or absence of P300 components are the focus of research on P300 EEG signal processing. Many studies have shown that epilepsy ...
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IPC IPC(8): A61B5/369A61B5/372
CPCA61B5/369A61B5/372
Inventor 沈继忠刘晓辰
Owner ZHEJIANG UNIV