Brain-computer interface target detection method based on decision fusion of P300 and ErrP
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R318; TN911. 7

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    Abstract:

    Aiming at the problem of limited detection accuracy in the application of brain-computer interface (BCI) technology in target detection, a new encoding and decoding method based on the decision layer fusion of P300 and error-related potential (ErrP) in eventrelated potential (ERP) was proposed. In the encoding aspect of the BCI system, the P300 and ErrP features are respectively evoked by the target image and visual feedback. In the decoding aspect, four schemes are used for target detection: individual P300 feature, individual ErrP feature, feature layer fusion of P300 and ErrP, and decision layer fusion of P300 and ErrP. The average results of 10 healthy subjects with four schemes show that the balance accuracy of decision layer fusion of P300 and ErrP is the highest, reaching 80. 03%±5. 20%, which is improved by 4. 38% compared with the method of using individual P300 feature and is improved by 11. 29% compared with the method of using individual ErrP feature. The feasibility of hybrid BCI technology in target detection tasks is verified.

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  • Received:
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  • Online: September 22,2023
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