大腦信號高精度採集技術：利用新型生物相容感測器和信號處理演算法，實現對大腦電信號的高精度採集，為準確解讀大腦意圖提供數據基礎。

深度學習與神經網路演算法：利用深度學習和神經網路演算法對大腦信號進行高效處理和解碼，提高腦機介面的準確性和即時性。

多模態腦機介面技術：整合腦電、磁共振成像（MRI）等多種模態的資訊，實現更全面、準確的腦意圖解讀。

個性化腦機介面技術：針對不同個體的大腦特徵，進行個性化的腦機介面設計和優化，提高用戶體驗和適用性。

High-precision brain signal acquisition technology: using new biocompatible sensor and signal processing algorithm to realize high-precision collection of brain electrical signal, providing data basis for accurate interpretation of brain intention.

Deep learning and neural network algorithm: Use deep learning and neural network algorithm to efficiently process and decode brain signals, and improve the accuracy and real-time performance of brain-computer interfaces.

Multimodal brain-computer interface technology: integrate electroencephalography, magnetic resonance imaging (MRI) and other modal information to achieve a more comprehensive and accurate interpretation of brain intention.

Personalized brain-computer interface technology: according to the brain characteristics of different individuals to improve user experience and applicability.