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Feasibility of using an Extended Kalman Filter for Motion Estimation based on Electrical Bioimpedance Sensing
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  • Yao Zhang ,
  • Kaat Van Assche ,
  • Mouloud Ourak ,
  • Eric Verschooten ,
  • Gianni Borghesan ,
  • Kenan Niu ,
  • Philip Joris ,
  • Emmanuel Vander Poorten
Yao Zhang
KU Leuven

Corresponding Author:[email protected]

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Kaat Van Assche
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Mouloud Ourak
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Eric Verschooten
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Gianni Borghesan
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Kenan Niu
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Philip Joris
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Emmanuel Vander Poorten
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Abstract

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.