From template to anchors: transfer of virtual pendulum posture control balance template to adaptive neuromuscular gait model increases walking stability

Biomechanical models with different levels of complexity are of advantage to understand the underlying principles of legged locomotion. Following a minimalistic approach of gradually increasing model complexity based on Template & Anchor concept, in this paper, a spring-loaded inverted pendulumbased walking model is extended by a rigid trunk, hip muscles and reflex control, called nmF (neuromuscular force modulated compliant hip) model. Our control strategy includes leg force feedback to activate hip muscles (originated from the FMCH approach), and a discrete linear quadratic regulator for adapting muscle reflexes. The nmF model demonstrates human-like walking kinematic and dynamic features such as the virtual pendulum (VP) concept, inherited from the FMCH model. Moreover, the robustness against postural perturbations is two times higher in the nmF model compared to the FMCH model and even further increased in the adaptive nmF model. This is due to the intrinsic muscle dynamics and the tuning of the reflex gains. With this, we demonstrate, for the first time, the evolution of mechanical template models (e.g. VP concept) to a more physiological level (nmF model). This shows that the template model can be successfully used to design and control robust locomotor systems with more realistic system behaviours

State-of-the-Art of Non-Radiative, Non-Visual Spine Sensing with a Focus on Sensing Forces, Vibrations and Bioelectrical Properties: A Systematic Review

In the research field of robotic spine surgery, there is a big upcoming momentum for surgeon-like autonomous behaviour and surgical accuracy in robotics which goes beyond the standard engineering notions such as geometric precision. The objective of this review is to present an overview of the state of the art in non-visual, non-radiative spine sensing for the enhancement of surgical techniques in robotic automation. It provides a vantage point that facilitates experimentation and guides new research projects to what has not been investigated or integrated in surgical robotics. Studies were identified, selected and processed according to the PRISMA guidelines. Relevant study characteristics that were searched for include the sensor type and measured feature, the surgical action, the tested sample, the method for data analysis and the system's accuracy of state identification. The 6DOF f/t sensor, the microphone and the electromyography probe were the most commonly used sensors in each category, respectively. The performance of the electromyography probe is unsatisfactory in terms of preventing nerve damage as it can only signal after the nerve is disturbed. Feature thresholding and artificial neural networks were the most common decision algorithms for state identification. The fusion of different sensor data in the decision algorithm improved the accuracy of state identification

An Augmented Reality-Based Interaction Scheme for Robotic Pedicle Screw Placement

Robot-assisted surgery is becoming popular in the operation room (OR) for, e.g., orthopedic surgery (among other surgeries). However, robotic executions related to surgical steps cannot simply rely on preoperative plans. Using pedicle screw placement as an example, extra adjustments are needed to adapt to the intraoperative changes when the preoperative planning is outdated. During surgery, adjusting a surgical plan is non-trivial and typically rather complex since the available interfaces used in current robotic systems are not always intuitive to use. Recently, thanks to technical advancements in head-mounted displays (HMD), augmented reality (AR)-based medical applications are emerging in the OR. The rendered virtual objects can be overlapped with real-world physical objects to offer intuitive displays of the surgical sites and anatomy. Moreover, the potential of combining AR with robotics is even more promising; however, it has not been fully exploited. In this paper, an innovative AR-based robotic approach is proposed and its technical feasibility in simulated pedicle screw placement is demonstrated. An approach for spatial calibration between the robot and HoloLens 2 without using an external 3D tracking system is proposed. The developed system offers an intuitive AR–robot interaction approach between the surgeon and the surgical robot by projecting the current surgical plan to the surgeon for fine-tuning and transferring the updated surgical plan immediately back to the robot side for execution. A series of bench-top experiments were conducted to evaluate system accuracy and human-related errors. A mean calibration error of 3.61 mm was found. The overall target pose error was 3.05 mm in translation and 1.12∘ in orientation. The average execution time for defining a target entry point intraoperatively was 26.56 s. This work offers an intuitive AR-based robotic approach, which could facilitate robotic technology in the OR and boost synergy between AR and robots for other medical applications

A Comparative Study for Control of Semi-Automatic Robotic-Assisted Ultrasound System in Spine Surgery

Ultrasound (US) imaging has been widely applied in different clinical scenarios thanks to its low-cost and non-radiative nature. Recently, robotic US has increasingly been investigated to produce 3D US reconstructions for navigation during surgical interventions. Robotics is considered of interest to address variable skills among human sonographers. Dedicated control strategies are needed to ensure high-quality robotic US reconstructions that are comparable or superior to those generated by human experts. The robot controller ought to establish human-like scanning maneuvers while maintaining tight skin contact and ensuring essential safety. In essence, this means that at all times, the robot should ensure contact while avoiding the application of excessive force on the patient. To acquire an improved understanding of what is an optimal control method, a comparative study on several admittance-based controllers was conducted while a semi-automatic path planning approach was used to realize automatic US scanning. The developed system was validated by scanning a synthetic phantom, compared with position and admittance control. The robotic US system with the proposed control applied a force lower than 3.83± 0.31 N while ensuring continuous US imaging. By defining the successful rate as a US image has more than 90% of soft tissue (i.e., ligament) length, the velocity-based admittance controller has more than 80% successful US imaging. Such an approach could contribute to the further development and uptake of robotic US systems in spine surgery or applications.</p

Development and evaluation of robot-assisted ultrasound navigation system for pedicle screw placement: An ex-vivo animal validation

PURPOSE Spinal instrumentation with pedicle screw placement (PSP) is an important surgical technique for spinal diseases. Accurate screw trajectory is a prerequisite for PSP. Ultrasound (US) imaging with robot-assisted system forms a non-radiative alternative to provide precise screw trajectory. This study reports on the development and assessment of US navigation for this application. METHODS A robot-assisted US reconstruction was proposed and an automatic CT-to-US registration algorithm was investigated, allowing the registration of screw trajectories. Experiments were conducted on ex-vivo lamb spines to evaluate system performance. RESULTS In total, 72 screw trajectories are measured, displaying an average position accuracy of 2.80 ± 1.14 mm and orientation accuracy of 1.38 ± 0.61°. CONCLUSION The experimental results demonstrate the feasibility of proposed US system. This work, although restricted to laboratory settings, encourages further exploration of the potential of this technology in clinical practice

Robot-assisted ultrasound reconstruction for spine surgery: from bench-top to pre-clinical study

Purpose: Robot-assisted ultrasound (rUS) systems have already been used to provide non-radiative three-dimensional (3D) reconstructions that form the basis for guiding spine surgical procedures. Despite promising studies on this technology, there are few studies that offer insight into the robustness and generality of the approach by verifying performance in various testing scenarios. Therefore, this study aims at providing an assessment of a rUS system, with technical details from experiments starting at the bench-top to the pre-clinical study. Methods: A semi-automatic control strategy was proposed to ensure continuous and smooth robotic scanning. Next, a U-Net-based segmentation approach was developed to automatically process the anatomic features and derive a high-quality 3D US reconstruction. Experiments were conducted on synthetic phantoms and human cadavers to validate the proposed approach. Results: Average deviations of scanning force were found to be 2.84±0.45 N on synthetic phantoms and to be 5.64±1.10 N on human cadavers. The anatomic features could be reliably reconstructed at mean accuracy of 1.28±0.87 mm for the synthetic phantoms and of 1.74±0.89 mm for the human cadavers. Conclusion: The results and experiments demonstrate the feasibility of the proposed system in a pre-clinical setting. This work is complementary to previous work, encouraging further exploration of the potential of this technology in in vivo studies