隨著積體電路的發展以及技術的成熟，應用在生物醫學方面的研究也
隨之增長。其中腦機介面在醫療診斷方面具有巨大潛力，通過分析腦部信
號，可以提供更準確的診斷結果，有助於早期檢測神經系統疾病、腦損傷
和其他神經相關疾病，例如帕金森氏症。這種技術的應用可提高醫學影像
學和神經學的準確性，有助於制定更有效的治療方案。
本研究的目標為研究植入式腦機介面晶片系統的前端電路並將其應用
於帕金森氏症的電刺激療法。主要目的為前端電路具有刺激假象消除的功
能，而刺激假象產生原因為刺激電極以及紀錄電極之間的電阻性和電容性
成分交互作用形成，在刺激電流通過器官組織內外的電解質溶液時，電信
號擴散到記錄電極下，並且因為超出放大器的輸入範圍，導致放大器的飽
和，從而造成訊號的失真，無法進行電刺激的判斷，進而導致紀錄神經訊
號無法正常進行，本論文旨在驗證其功能的正確性，並且在下線後量測
時，比較電路模擬結果和量測結果的不同，以此驗證晶片功能正確性。
本論文將沿用已畢業學姊的部分電路設計，並且將其架構進行優化和
改良也加入了其他子電路，以此達到期望的功能，將在後續進行更深入的
介紹，在電路模擬結果中，已能降低刺激假象達到順利進行神經訊號的紀
錄的效果。

As integrated circuit technology advances, biomedical research grows,
particularly in brain-machine interfaces (BMIs) for medical diagnosis. Analyzing
brain signals allows for accurate diagnostics, aiding in early detection of
neurological diseases like Parkinson's. This technology improves medical
imaging precision and neuroscience, contributing to more effective treatment
plans.
The objective of this study is to investigate the front-end circuits of
implantable brain-machine interface (BMI) chips for application in electrical
stimulation therapy for Parkinson's disease. The primary goal is to eliminate
stimulation artifacts, which are caused by the interaction between resistive and
capacitive components of the stimulation and recording electrodes. These
artifacts result in signal distortion and amplifier saturation, thereby impairing the
accurate recording of neural signals. This thesis aims to validate the functionality
of the proposed system. Following fabrication, the circuit simulation results will
be compared with measurement outcomes to ensure the chip's correct operation
and effectiveness in artifact elimination.
This study will adopt some sub-circuits from a previous graduate student and
optimize the structure while incorporating additional sub-circuits to achieve the
desired functionality. Further details will be elaborated in subsequent sections. In
circuit simulations, the reduction of stimulation artifacts has been achieved,
facilitating smooth recording of neural signals.

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