A Closed-Loop Automated Craniotomy System With Real-Time Bio-Impedance Feedback

Abstract

Cranial microsurgery is a prerequisite for neuroscience research, which provides an accessible brain for neural recording and optogenetic stimulation. As the scale of electrode implantation increases, massive delicate craniotomies are required to perform on the submillimeter-thick skull of small animals (e.g., mice). Automated craniotomy (AMC) is ideal for improving surgery efficiency and ensuring consistent results. However, due to the lack of effective feedback, the current AMC platforms are prone to over-drilling and injuring brain tissues. Fragile and ultrathin skulls of small objects also make it hard to integrate suitable sensors into the end-effector for accurate perception. Thus, this article proposes an integrated electrical bioimpedance measurement (EBIM) solution for the closed-loop AMC. A sensing drill and a custom EBIM device are implemented to form reliable electrical contact with the object and accurately measure the impedance. After evaluating the EBIM device’s accuracy (< 2% relative error) and stability, we provide a modified judgment signal for breakthrough detection and further simulate closed-loop craniotomies on an equivalent model. The experimental results demonstrate that the proposed system can achieve sensitive breakthrough detection (< 0.1 s delay at 100 Hz excitation) and consistent drilling depth ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10.3 \mu \text{m}$ </tex-math></inline-formula> deviation with a 10-mm/min feed rate) in contrast to the gold standard (LCR meter).