Patch-clamp is a widely used technique to record the electrophysiological activity of neurons in vivo. However, establishing and maintaining a long-term stable recording is difficult due to neuronal motion induced by physiological motion. This abstract proposes an Extended Kalman Filter (EKF) method for motion estimation based on Electrical Bioimpedance (EBI) sensing. The results show that with EBI, the EKF could estimate the motion with high precision (RMSE = 0.022V) and robustness (STD = 0.0028V) in real-time.