Model-based trajectory tracking of a compliant continuum robot.

Introduction: Compliant mechanisms, especially continuum robots, are becoming integral to advancements in minimally invasive surgery due to their ability to autonomously navigate natural pathways, significantly reducing collision severity. A major challenge lies in developing an effective control strategy to accurately reflect their behavior for enhanced operational precision. Methods: This study examines the trajectory tracking capabilities of a tendon-driven continuum robot at its tip. We introduce a novel feedforward control methodology that leverages a mathematical model based on Cosserat rod theory. To mitigate the computational challenges inherent in such models, we implement an implicit time discretization strategy. This approach simplifies the governing equations into space-domain ordinary differential equations, facilitating real-time computational efficiency. The control strategy is devised to enable the robot tip to follow a dynamically prescribed trajectory in two dimensions. Results: The efficacy of the proposed control method was validated through experimental tests on six different demand trajectories, with a motion capture system employed to assess positional accuracy. The findings indicate that the robot can track trajectories with an accuracy within 9.5%, showcasing consistent repeatability across different runs. Discussion: The results from this study mark a significant step towards establishing an efficient and precise control methodology for compliant continuum robots. The demonstrated accuracy and repeatability of the control approach significantly enhance the potential of these robots in minimally invasive surgical applications, paving the way for further research and development in this field.

A Deep Learning Model with a Self-Attention Mechanism for Leg Joint Angle Estimation across Varied Locomotion Modes.

Conventional trajectory planning for lower limb assistive devices usually relies on a finite-state strategy, which pre-defines fixed trajectory types for specific gait events and activities. The advancement of deep learning enables walking assistive devices to better adapt to varied terrains for diverse users by learning movement patterns from gait data. Using a self-attention mechanism, a temporal deep learning model is developed in this study to continuously generate lower limb joint angle trajectories for an ankle and knee across various activities. Additional analyses, including using Fast Fourier Transform and paired t-tests, are conducted to demonstrate the benefits of the proposed attention model architecture over the existing methods. Transfer learning has also been performed to prove the importance of data diversity. Under a 10-fold leave-one-out testing scheme, the observed attention model errors are 11.50% (±2.37%) and 9.31% (±1.56%) NRMSE for ankle and knee angle estimation, respectively, which are small in comparison to other studies. Statistical analysis using the paired t-test reveals that the proposed attention model appears superior to the baseline model in terms of reduced prediction error. The attention model also produces smoother outputs, which is crucial for safety and comfort. Transfer learning has been shown to effectively reduce model errors and noise, showing the importance of including diverse datasets. The suggested joint angle trajectory generator has the potential to seamlessly switch between different locomotion tasks, thereby mitigating the problem of detecting activity transitions encountered by the traditional finite-state strategy. This data-driven trajectory generation method can also reduce the burden on personalization, as traditional devices rely on prosthetists to experimentally tune many parameters for individuals with diverse gait patterns.

Deep learning with an attention mechanism for continuous biomechanical motion estimation across varied activities.

Reliable estimation of desired motion trajectories plays a crucial part in the continuous control of lower extremity assistance devices such as prostheses and orthoses. Moreover, reliable estimation methods are also required to predict hard-to-measure biomechanical quantities (e.g., joint contact moment/force) for use in sports injury science. Recognising that human locomotion is an inherently time-sequential and limb-synergetic behaviour, this study investigates models and learning algorithms for predicting the motion of a subject's leg from the motion of complementary limbs. The novel deep learning model architectures proposed are based on the Long Short-Term Memory approach with the addition of an attention mechanism. A dataset comprising Inertial Measurement Unit signals from 21 subjects traversing varied terrains was used, including stair ascent/descent, ramp ascent/descent, stopped, level-ground walking and the transitions between these conditions. Fourier Analysis is deployed to evaluate the model robustness, in addition to assessing time-based prediction errors. The experiment on three unseen test participants suggests that the branched neural network structure is preferred to tackle the multioutput problem, and the inclusion of an attention mechanism demonstrates improved performance in terms of accuracy, robustness and network size. An experimental comparison found that 57% of the model parameters were not needed after adding attention layers meanwhile the prediction error is lower than the LSTM model without attention mechanism. The attention model has errors of 9.06% and 7.64% (normalised root mean square error) for ankle and hip acceleration prediction respectively. Also, less high-frequency noise is present in the attention model predictions. We conclude that the internal structure of the proposed deep learning model is justified, principally the benefit of using an attention mechanism. Experimental results for biomechanical motion estimation are obtained, showing greater accuracy than only with LSTM. The trained attention model can be used throughout despite transitioning between terrain types. Such a model will be useful in, for example, the control of lower-limb prostheses, instead of the need to identify and switch between different trajectory generators for different walking modes.

Parameter Reduction and Optimisation for Point Cloud and Occupancy Mapping Algorithms.

Occupancy mapping is widely used to generate volumetric 3D environment models from point clouds, informing a robotic platform which parts of the environment are free and which are not. The selection of the parameters that govern the point cloud generation algorithms and mapping algorithms affects the process and the quality of the final map. Although previous studies have been reported in the literature on optimising major parameter configurations, research in the process to identify optimal parameter sets to achieve best occupancy mapping performance remains limited. The current work aims to fill this gap with a two-step principled methodology that first identifies the most significant parameters by conducting Neighbourhood Component Analysis on all parameters and then optimise those using grid search with the area under the Receiver Operating Characteristic curve. This study is conducted on 20 data sets with specially designed targets, providing precise ground truths for evaluation purposes. The methodology is tested on OctoMap with point clouds created by applying StereoSGBM on the images from a stereo camera. A clear indication can be seen that mapping parameters are more important than point cloud generation parameters. Moreover, up to 15% improvement in mapping performance can be achieved over default parameters.

An Integrated Kinematic Modeling and Experimental Approach for an Active Endoscope.

Continuum robots are a type of robotic device that are characterized by their flexibility and dexterity, thus making them ideal for an active endoscope. Instead of articulated joints they have flexible backbones that can be manipulated remotely, usually through tendons secured onto structures attached to the backbone. This structure makes them lightweight and ideal to be miniaturized for endoscopic applications. However, their flexibility poses technical challenges in the modeling and control of these devices, especially when closed-loop control is needed, as is the case in medical applications. There are two main approaches in the modeling of continuum robots, the first is to theoretically model the behavior of the backbone and the interaction with the tendons, while the second is to collect experimental observations and retrospectively apply a model that can approximate their apparent behavior. Both approaches are affected by the complexity of continuum robots through either model accuracy/computational time (theoretical method) or missing complex system interactions and lacking expandability (experimental method). In this work, theoretical and experimental descriptions of an endoscopic continuum robot are merged. A simplified yet representative mathematical model of a continuum robot is developed, in which the backbone model is based on Cosserat rod theory and is coupled to the tendon tensions. A robust numerical technique is formulated that has low computational costs. A bespoke experimental facility with precise automated motion of the backbone via the precise control of tendon tension, leads to a robust and detailed description of the system behavior provided through a contactless sensor. The resulting facility achieves a real-world mean positioning error of 3.95% of the backbone length for the examined range of tendon tensions which performs favourably to existing approaches. Moreover, it incorporates hysteresis behavior that could not be predicted by the theoretical modeling alone, reinforcing the benefits of the hybrid approach. The proposed workflow is theoretically grounded and experimentally validated allowing precise prediction of the continuum robot behavior, adhering to realistic observations. Based on this accurate estimation and the fact it is geometrically agnostic enables the proposed model to be scaled for various robotic endoscopes.

A Robotic Test Rig for Performance Assessment of Prosthetic Joints.

Movement within the human body is made possible by joints connecting two or more elements of the musculoskeletal system. Losing one or more of these connections can seriously limit mobility, which in turn can lead to depression and other mental issues. This is particularly pertinent due to a dramatic increase in the number of lower limb amputations resulting from trauma and diseases such as diabetes. The ideal prostheses should re-establish the functions and movement of the missing body part of the patient. As a result, the prosthetic solution has to be tested stringently to ensure effective and reliable usage. This paper elaborates on the development, features, and suitability of a testing rig that can evaluate the performance of prosthetic and robotic joints via cyclic dynamic loading on their complex movements. To establish the rig's validity, the knee joint was chosen as it provides both compound support and movement, making it one of the major joints within the human body, and an excellent subject to ensure the quality of the prosthesis. Within the rig system, a motorised lead-screw simulates the actuation provided by the hamstring-quadricep antagonist muscle pair and the flexion experienced by the joint. Loads and position are monitored by a load cell and proximity sensors respectively, ensuring the dynamics conform with the geometric model and gait analysis. Background: Robotics, Prosthetics, Mechatronics, Assisted Living. Methods: Gait Analysis, Computer Aided Design, Geometry Models. Conclusion: Modular Device, Streamlining Rehabilitation.

An Occupancy Mapping Method Based on K-Nearest Neighbours.

OctoMap is an efficient probabilistic mapping framework to build occupancy maps from point clouds, representing 3D environments with cubic nodes in the octree. However, the map update policy in OctoMap has limitations. All the nodes containing points will be assigned with the same probability regardless of the points being noise, and the probability of one such node can only be increased with a single measurement. In addition, potentially occupied nodes with points inside but traversed by rays cast from the sensor to endpoints will be marked as free. To overcome these limitations in OctoMap, the current work presents a mapping method using the context of neighbouring points to update nodes containing points, with occupancy information of a point represented by the average distance from a point to its k-Nearest Neighbours. A relationship between the distance and the change in probability is defined with the Cumulative Density Function of average distances, potentially decreasing the probability of a node despite points being present inside. Experiments are conducted on 20 data sets to compare the proposed method with OctoMap. Results show that our method can achieve up to 10% improvement over the optimal performance of OctoMap.

Design and Evaluation of a Percutaneous Fragment Manipulation Device for Minimally Invasive Fracture Surgery.

Reduction of fractures in the minimally invasive (MI) manner can avoid risks associated with open fracture surgery. The MI approach requires specialized tools called percutaneous fragment manipulation devices (PFMD) to enable surgeons to safely grasp and manipulate fragments. PFMDs developed for long-bone manipulation are not suitable for intra-articular fractures where small bone fragments are involved. With this study, we offer a solution to potentially move the current fracture management practice closer to the use of a MI approach. We investigate the design and testing of a new PFMD design for manual as well as robot-assisted manipulation of small bone fragments. This new PFMD design is simulated using FEA in three loading scenarios (force/torque: 0 N/2.6 Nm, 75.7 N/3.5 N, 147 N/6.8 Nm) assessing structural properties, breaking points, and maximum bending deformations. The PFMD is tested in a laboratory setting on Sawbones models (0 N/2.6 Nm), and on ex-vivo swine samples (F = 80 N ± 8 N, F = 150 ± 15 N). A commercial optical tracking system was used for measuring PFMD deformations under external loading and the results were verified with an electromagnetic tracking system. The average error difference between the tracking systems was 0.5 mm, being within their accuracy limits. Final results from reduction maneuvers performed both manually and with the robot assistance are obtained from 7 human cadavers with reduction forces in the range of (F = 80 N ± 8 N, F = 150 ± 15 N, respectively). The results show that structurally, the system performs as predicted by the simulation results. The PFMD did not break during ex-vivo and cadaveric trials. Simulation, laboratory, and cadaveric tests produced similar results regarding the PFMD bending. Specifically, for forces applied perpendicularly to the axis of the PFMD of 80 N ± 8 N deformations of 2.8, 2.97, and 3.06 mm are measured on the PFMD, while forces of 150 ± 15 N produced deformations of 5.8, 4.44, and 5.19 mm. This study has demonstrated that the proposed PFMD undergoes predictable deformations under typical bone manipulation loads. Testing of the device on human cadavers proved that these deformations do not affect the anatomic reduction quality. The PFMD is, therefore, suitable to reliably achieve and maintain fracture reductions, and to, consequently, allow external fracture fixation.

Robot-Assisted Fracture Surgery: Surgical Requirements and System Design.

The design of medical devices is a complex and crucial process to ensure patient safety. It has been shown that improperly designed devices lead to errors and associated accidents and costs. A key element for a successful design is incorporating the views of the primary and secondary stakeholders early in the development process. They provide insights into current practice and point out specific issues with the current processes and equipment in use. This work presents how information from a user-study conducted in the early stages of the RAFS (Robot Assisted Fracture Surgery) project informed the subsequent development and testing of the system. The user needs were captured using qualitative methods and converted to operational, functional, and non-functional requirements based on the methods derived from product design and development. This work presents how the requirements inform a new workflow for intra-articular joint fracture reduction using a robotic system. It is also shown how the various elements of the system are developed to explicitly address one or more of the requirements identified, and how intermediate verification tests are conducted to ensure conformity. Finally, a validation test in the form of a cadaveric trial confirms the ability of the designed system to satisfy the aims set by the original research question and the needs of the users.

Image-Guided Surgical Robotic System for Percutaneous Reduction of Joint Fractures.

Complex joint fractures often require an open surgical procedure, which is associated with extensive soft tissue damages and longer hospitalization and rehabilitation time. Percutaneous techniques can potentially mitigate these risks but their application to joint fractures is limited by the current sub-optimal 2D intra-operative imaging (fluoroscopy) and by the high forces involved in the fragment manipulation (due to the presence of soft tissue, e.g., muscles) which might result in fracture malreduction. Integration of robotic assistance and 3D image guidance can potentially overcome these issues. The authors propose an image-guided surgical robotic system for the percutaneous treatment of knee joint fractures, i.e., the robot-assisted fracture surgery (RAFS) system. It allows simultaneous manipulation of two bone fragments, safer robot-bone fixation system, and a traction performing robotic manipulator. This system has led to a novel clinical workflow and has been tested both in laboratory and in clinically relevant cadaveric trials. The RAFS system was tested on 9 cadaver specimens and was able to reduce 7 out of 9 distal femur fractures (T- and Y-shape 33-C1) with acceptable accuracy (≈1 mm, ≈5°), demonstrating its applicability to fix knee joint fractures. This study paved the way to develop novel technologies for percutaneous treatment of complex fractures including hip, ankle, and shoulder, thus representing a step toward minimally-invasive fracture surgeries.

Intra-operative fiducial-based CT/fluoroscope image registration framework for image-guided robot-assisted joint fracture surgery.

PURPOSE: Joint fractures must be accurately reduced minimising soft tissue damages to avoid negative surgical outcomes. To this regard, we have developed the RAFS surgical system, which allows the percutaneous reduction of intra-articular fractures and provides intra-operative real-time 3D image guidance to the surgeon. Earlier experiments showed the effectiveness of the RAFS system on phantoms, but also key issues which precluded its use in a clinical application. This work proposes a redesign of the RAFS's navigation system overcoming the earlier version's issues, aiming to move the RAFS system into a surgical environment. METHODS: The navigation system is improved through an image registration framework allowing the intra-operative registration between pre-operative CT images and intra-operative fluoroscopic images of a fractured bone using a custom-made fiducial marker. The objective of the registration is to estimate the relative pose between a bone fragment and an orthopaedic manipulation pin inserted into it intra-operatively. The actual pose of the bone fragment can be updated in real time using an optical tracker, enabling the image guidance. RESULTS: Experiments on phantom and cadavers demonstrated the accuracy and reliability of the registration framework, showing a reduction accuracy (sTRE) of about [Formula: see text] (phantom) and [Formula: see text] (cadavers). Four distal femur fractures were successfully reduced in cadaveric specimens using the improved navigation system and the RAFS system following the new clinical workflow (reduction error [Formula: see text], [Formula: see text]. CONCLUSION: Experiments showed the feasibility of the image registration framework. It was successfully integrated into the navigation system, allowing the use of the RAFS system in a realistic surgical application.

Navigation system for robot-assisted intra-articular lower-limb fracture surgery.

PURPOSE: In the surgical treatment for lower-leg intra-articular fractures, the fragments have to be positioned and aligned to reconstruct the fractured bone as precisely as possible, to allow the joint to function correctly again. Standard procedures use 2D radiographs to estimate the desired reduction position of bone fragments. However, optimal correction in a 3D space requires 3D imaging. This paper introduces a new navigation system that uses pre-operative planning based on 3D CT data and intra-operative 3D guidance to virtually reduce lower-limb intra-articular fractures. Physical reduction in the fractures is then performed by our robotic system based on the virtual reduction. METHODS: 3D models of bone fragments are segmented from CT scan. Fragments are pre-operatively visualized on the screen and virtually manipulated by the surgeon through a dedicated GUI to achieve the virtual reduction in the fracture. Intra-operatively, the actual position of the bone fragments is provided by an optical tracker enabling real-time 3D guidance. The motion commands for the robot connected to the bone fragment are generated, and the fracture physically reduced based on the surgeon's virtual reduction. To test the system, four femur models were fractured to obtain four different distal femur fracture types. Each one of them was subsequently reduced 20 times by a surgeon using our system. RESULTS: The navigation system allowed an orthopaedic surgeon to virtually reduce the fracture with a maximum residual positioning error of [Formula: see text] (translational) and [Formula: see text] (rotational). Correspondent physical reductions resulted in an accuracy of 1.03 ± 0.2 mm and [Formula: see text], when the robot reduced the fracture. CONCLUSIONS: Experimental outcome demonstrates the accuracy and effectiveness of the proposed navigation system, presenting a fracture reduction accuracy of about 1 mm and [Formula: see text], and meeting the clinical requirements for distal femur fracture reduction procedures.

Vision-based real-time position control of a semi-automated system for robot-assisted joint fracture surgery.

PURPOSE: Joint fracture surgery quality can be improved by robotic system with high-accuracy and high-repeatability fracture fragment manipulation. A new real-time vision-based system for fragment manipulation during robot-assisted fracture surgery was developed and tested. METHODS: The control strategy was accomplished by merging fast open-loop control with vision-based control. This two-phase process is designed to eliminate the open-loop positioning errors by closing the control loop using visual feedback provided by an optical tracking system. Evaluation of the control system accuracy was performed using robot positioning trials, and fracture reduction accuracy was tested in trials on ex vivo porcine model. RESULTS: The system resulted in high fracture reduction reliability with a reduction accuracy of 0.09 mm (translations) and of [Formula: see text] (rotations), maximum observed errors in the order of 0.12 mm (translations) and of [Formula: see text] (rotations), and a reduction repeatability of 0.02 mm and [Formula: see text]. CONCLUSIONS: The proposed vision-based system was shown to be effective and suitable for real joint fracture surgical procedures, contributing a potential improvement of their quality.

Powered exoskeleton with palm degrees of freedom for hand rehabilitation.

Robotic rehabilitation is a currently underutilised field with the potential to allow huge cost savings within healthcare. Existing rehabilitation exoskeletons oversimplify the importance of movement of the hand while undertaking everyday tasks. Within this study, an investigation was undertaken to establish the extent to which the degrees of freedom within the palm affect ability to undertake everyday tasks. Using a 5DT data glove, bend sensing resistors and restrictors of palm movement, 20 participants were recruited to complete tasks that required various hand shapes. Collected data was processed and palm arching trends were identified for each grasping task. It was found that the extent of utilizing arches in the palm varied with each exercise, but was extensively employed throughout. An exoskeleton was subsequently designed with consideration of the identified palm shapes. This design included a number of key features that accommodated for a variety of hand sizes, a novel thumb joint and a series of dorsally mounted servos. Initial exoskeleton testing was undertaken by having a participant complete the same exercises while wearing the exoskeleton. The angles formed by the user during this process were then compared to those recorded by 2 other participants who had completed the same tasks without exoskeleton. It was found that the exoskeleton was capable of forming the required arches for completing the tasks, with differences between participants attributed to individual ergonomic differences.

Preliminary analysis of force-torque measurements for robot-assisted fracture surgery.

Our group at Bristol Robotics Laboratory has been working on a new robotic system for fracture surgery that has been previously reported [1]. The robotic system is being developed for distal femur fractures and features a robot that manipulates the small fracture fragments through small percutaneous incisions and a robot that re-aligns the long bones. The robots controller design relies on accurate and bounded force and position parameters for which we require real surgical data. This paper reports preliminary findings of forces and torques applied during bone and soft tissue manipulation in typical orthopaedic surgery procedures. Using customised orthopaedic surgical tools we have collected data from a range of orthopaedic surgical procedures at Bristol Royal Infirmary, UK. Maximum forces and torques encountered during fracture manipulation which involved proximal femur and soft tissue distraction around it and reduction of neck of femur fractures have been recorded and further analysed in conjunction with accompanying image recordings. Using this data we are establishing a set of technical requirements for creating safe and dynamically stable minimally invasive robot-assisted fracture surgery (RAFS) systems.

Deep wound infection after a trochanteric fracture internal fixation presenting with hip dislocation: a case report.

We report a rare case of posterior hip dislocation after a low energy trauma. The patient sustained a trochanteric fracture in the same hip six months ago, which was fixed using a sliding hip screw and had healed. At surgery a deep wound infection was found and a methicillin-resistant Staphylococcus epidermidis (MRSE) was cultured. After thorough debridement, an excisional arthroplasty was decided. The patient received specific intravenous antibiotics and after six weeks a total hip arthroplasty was done. In three years follow-up the patients presented with a fully functional hip without any signs of infection. Hip dislocation after a trochanteric fracture internal fixation is rare complication associated with high morbidity and mortality. Infection eradication and a second stage arthroplasty can be life and limb saving.

Massive haemorrhage due to minimally displaced pubic ramus fracture.

Fractures of the pubic ramus are commonly seen in the emergency room, but they are thought to be minor injuries. Occasionally, these fractures might be associated with massive haemorrhage. Here we report a case of bilateral obturator artery damage due to minimal displaced pubic ramus fracture.

Hip screw lateral migration with no cut-out or non-union implication: a case report.

Hip screw migration of peritrochanteric fracture fixation devices is a described complication in English literature. Medial migration occupies the majority of these cases whereas lateral migration is rare. We report the case of an 85-year-old woman whose intramedullary osteosynthesis of a trochanteric fracture was complicated by hip screw lateral migration. Mobilization was not influenced and no cut-out or non-union was detected. The migrated hip screw was easily removed and the discomfort vanished. The need for adequate surgical technique and radiographic examination after re-injuries even if the patient remains ambulatory is emphasised.

Removal of broken distal intramedullary nail with a simple method: a case report.

Breakage of the intramedullary nail has long been recognized as an uncommon complication of intamedullary nailing of long bones. Retrieval of the distal fragment of a broken nail is a challenging problem. The surgeon needs to be familiar with as many methods of distal fragment extraction as possible. Herein we report a case of broken intramedullay nail, which was removed with a small reamer, wedged into the distal segment of the nail.

Intra-articular knee haemangioma originating from the anterior cruciate ligament: a case report.

INTRODUCTION: Synovial haemangioma is a rare intra-articular benign tumour, which may arise from any synovium-lined surface, but particularly in the knee joint. Synovial haemangioma originating from the anterior cruciate ligament has not been reported previously. CASE PRESENTATION: A 34-year-old man presented with a history of intermittent knee pain, locking and swelling. CONCLUSION: Knee intra-articular haemangioma, a very rare benign tumour, is often misdiagnosed. Magnetic resonance imaging is effective in detecting this lesion and should be performed in cases of persistent knee swelling and pain.