Patch clamping of neurons is a powerful technique used to understand the electrophysiological signals of the brain and advance research into neurological disorders. In in vivo patch clamping, a micropipette is clamped onto the membrane of a neuronal cell body. This technique is difficult and timeconsuming to perform due to the challenges in approaching neurons because of their small size, the absence of visual feedback, and physiologically induced movement caused by heartbeat and breathing. This paper presents a model-based motion compensation algorithm relying solely on electrical bio-impedance (EBI) sensing. The ultimate goal is to cancel out the relative motion between the patch-pipette and the neuron to increase in vivo patch clamping efficiency. In the proposed algorithm, EBI-pipette measurements in response to physiologically induced motions are used to impose on the pipette a motion similar to that of the neuron. The model is based on the assumption that physiological motion can be approximated by a sinusoidal model with three parameters: frequency, phase, and amplitude. The developed compensation algorithm was evaluated in an experimental setup and results yielded a compensation efficiency of (85.5 ± 3.6)%, (81.9 ± 4.0)%, (75.9 ± 1.8)% for artificially imposed motions of 1 Hz, 2 Hz and 3 Hz with an amplitude of 31 µm. The algorithm also demonstrated that it can adjust its motion characterization in real time to changes in amplitude, phase, and also frequency.

<p>Ultrasound (US) scanning has become increasingly popular in the medical industry as it provides radiation-free, compact and real time imaging solutions for diagnosis and intraoperative navigation during interventions such as pedicle screw placement (PSP).  Robotic ultrasound scanning systems have shown to increase the imaging quality by maintaining constant contact between the US probe and the skin surface. To image bones, US waves travel through the skin and reflect or deflect on the bone depending on the inclination of the surface. Reflection and hence intensity of the image is maximal when the incident US wave is perpendicular to the bone surface. Therefore, optimising the orientation of the US probe with respect to the underlying anatomy could be especially beneficial in visualising complex bony structures such as the lumbar spine in which features such as the spinous process are rarely visualised when scanning at an angle perpendicular to the skin. Therefore, this abstract presents a robotic path planning approach that optimises the orientation of the US probe to maximise the ultrasound image quality and hence the resulting 3D reconstructions of complex bony structures such as the lumbar spine.</p>

<p>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.</p>

<p>This study presents the first automated robotic system for PSP without the need for an external tracking system. The proposed system utilizes a U-Net-based framework to segment 2d US images and reconstruct 3D anatomy features, enabling visualization of the spinal structure. Then, the desired screw trajectories are automatically registered to the 3D reconstruction. By employing this robot-assisted system, the reliance on guide-tube-based approaches is eliminated, reducing the physical demands of the procedure and allowing the surgeon to focus more on planning and evaluation rather than execution.<br> </p> <p>Experimental evaluation on two lamb vertebrae yielded four screw trajectories. The mean 3D error is 2.78 mm at the entry points and 4.82 mm at the stop points. Compared to commercial robotic systems, the use of non-radiation imaging decreases the second harm to the patient and surgeons. Meanwhile, it gets rid of the bone pin, which can lead to an incision in the patient's body. </p>

<p>This study presents the first automated robotic system for PSP without the need for an external tracking system. The proposed system utilizes a U-Net-based framework to segment 2d US images and reconstruct 3D anatomy features, enabling visualization of the spinal structure. Then, the desired screw trajectories are automatically registered to the 3D reconstruction. By employing this robot-assisted system, the reliance on guide-tube-based approaches is eliminated, reducing the physical demands of the procedure and allowing the surgeon to focus more on planning and evaluation rather than execution.<br> </p> <p>Experimental evaluation on two lamb vertebrae yielded four screw trajectories. The mean 3D error is 2.78 mm at the entry points and 4.82 mm at the stop points. Compared to commercial robotic systems, the use of non-radiation imaging decreases the second harm to the patient and surgeons. Meanwhile, it gets rid of the bone pin, which can lead to an incision in the patient's body. </p>