Robot-guided osteotomy in fibula free flap mandibular reconstruction: a preclinical study

Various methods currently exist to guide fibular osteotomy positioning in fibula free flap mandibular reconstruction, but patient-specific navigation methods and cutting guides require experience, and may be time-consuming and/or expensive. This study describes a robot-guided osteotomy technique for mandible reconstruction using a fibula free flap according to virtual preoperative planning. The method was assessed on five 3D-printed models and a cadaveric model. The precision of the robot-guided osteotomy was evaluated by measuring the deviations between the lengths and angles of the fragments obtained and those of the virtual planning. The average deviation of the anterior and posterior crest lengths was 0.42 ± 0.29 mm for the 3D-printed models and 1.00 ± 0.53 mm for the cadaveric model. The average angle deviation was 1.90 ± 1.22° and 1.94 ± 0.69° for the 3D-printed and cadaveric models, respectively. The results of this preclinical study revealed that fibular osteotomy positioning guidance using a robot-positioned cutting guide may be a precise, easy-to-use technique that could be tailored for fibula free flap mandibular reconstruction.

Contactless surface registration of featureless anatomy using structured light camera: application to fibula navigation in mandible reconstruction

PURPOSE

Mandibular reconstruction using fibula free flap is a challenging surgical procedure. To assist osteotomies, computer-assisted surgery (CAS) can be used. Nevertheless, precise registration is required and often necessitates anchored markers that disturb the patient and clinical flow. This work proposes a new contactless surface-based method adapted to featureless anatomies such as fibula to achieve a fast, precise, and reproducible registration.

METHODS

Preoperatively, a CT-scan of the patient is realized and osteotomies are virtually planned. During surgery, a structured light camera digitizes the fibula. The obtained intraoperative point cloud is coarsely registered with the preoperative model using 3 points defined in the CT-scan and located on the patient's bone with a laser beam. Then, a fine registration is performed using an ICP algorithm. The registration accuracy was evaluated comparing the position of points engraved in a 3D-printed fibula with their position in the registered model and evaluating resulting osteotomies. Accuracy and execution time were compared to a conventional stylus-based registration method. The work was validated in vivo.

RESULTS

The experiment performed on a 3D-printed model showed that execution time is equivalent to surface-based registration using a stylus, with a better accuracy (mean TRE of 0.9 mm vs 1.3 mm using stylus) and guarantee good osteotomies. The preliminary in vivo study proved the feasibility of the method.

CONCLUSION

The proposed contactless surface-based registration method using structured light camera gave promising results in terms of accuracy and execution speed and should be useful to implement CAS for mandibular reconstruction.

Miniaturized Endoscopic 2D US Transducer for Volumetric Ultrasound Imaging of the Auditory System

OBJECTIVE

In this paper, we focus on the carrying out and validation of minimally invasive three-dimensional (3D) ultrasound (US) imaging of the auditory system, which is based on a new miniaturized endoscopic 2D US transducer.

METHODS

This unique probe consists of a 18 MHz 24 elements curved array transducer with a distal diameter of 4 mm so it can be inserted into the external auditory canal. Typical acquisition is achieved by rotating such a transducer around its own axis using a robotic platform. Reconstruction of a US volume from the set of acquired B-scans during the rotation is then performed using scan-conversion. The accuracy of the reconstruction procedure is evaluated using a dedicated phantom that includes a set of wires as reference geometry.

RESULTS

Twelve acquisitions obtained from different probe poses are compared to a micro-computed tomographic model of the phantom, leading to a maximum error of 0.20 mm. Additionally, acquisitions with a cadaveric head highlight the clinical applicability of this set up. Structures of the auditory system such as the ossicles and the round window can be identified from the obtained 3D volumes.

CONCLUSION

These results confirm that our technique enables the accurate imaging of the middle and inner ears without having to deteriorate the surrounding bone.

SIGNIFICANCE

Since US is a real-time, wide available and non-ionizing imaging modality, our acquisition setup could facilitate the minimally invasive diagnosis and surgical navigation for otology in a fast, cost-effective and safe way.

sEMG-based Motion Recognition for Robotic Surgery Training - A Preliminary Study

Robotic surgery represents a major breakthrough in the evolution of medical technology. Accordingly, efficient skill training and assessment methods should be developed to meet the surgeon's need of acquiring such robotic skills over a relatively short learning curve in a safe manner. Different from conventional training and assessment methods, we aim to explore the surface electromyography (sEMG) signal during the training process in order to obtain semantic and interpretable information to help the trainee better understand and improve his/her training performance. As a preliminary study, motion primitive recognition based on sEMG signal is studied in this work. Using machine learning (ML) technique, it is shown that the sEMG-based motion recognition method is feasible and promising for hand motions along 3 Cartesian axes in the virtual reality (VR) environment of a commercial robotic surgery training platform, which will hence serve as the basis for new robotic surgical skill assessment criterion and training guidance based on muscle activity information. Considering certain motion patterns were less accurately recognized than others, more data collection and deep learning-based analysis will be carried out to further improve the recognition accuracy in future research.

Sparse-view CBCT reconstruction via weighted Schatten p-norm minimization

A novel iterative algorithm is proposed for sparse-view cone beam computed tomography (CBCT) reconstruction based on the weighted Schatten p-norm minimization (WSNM). By using the half quadratic splitting, the sparse-view CBCT reconstruction task is decomposed into two sub-problems that can be solved through alternating iteration: simple reconstruction and image denoising. The WSNM that fits well with the low-rank hypothesis of CBCT data is introduced to improve the denoising sub-problem as a regularization term. The experimental results based on the digital brain phantom and clinical CT data indicated the advantages of the proposed algorithm in both structural information preservation and artifacts suppression, which performs better than the classical algorithms in quantitative and qualitative evaluations.

HFUS Imaging of the Cochlea: A Feasibility Study for Anatomical Identification by Registration with MicroCT

Cochlear implantation consists in electrically stimulating the auditory nerve by inserting an electrode array inside the cochlea, a bony structure of the inner ear. In the absence of any visual feedback, the insertion results in many cases of damages of the internal structures. This paper presents a feasibility study on intraoperative imaging and identification of cochlear structures with high-frequency ultrasound (HFUS). 6 ex-vivo guinea pig cochleae were subjected to both US and microcomputed tomography (µCT) we respectively referred as intraoperative and preoperative modalities. For each sample, registration based on simulating US from the scanner was performed to allow a precise matching between the visible structures. According to two otologists, the procedure led to a target registration error of 0.32 mm ± 0.05. Thanks to referring to a better preoperative anatomical representation, we were able to intraoperatively identify the modiolus, both scalae vestibuli and tympani and deduce the location of the basilar membrane, all of which is of great interest for cochlear implantation. Our main objective is to extend this procedure to the human case and thus provide a new tool for inner ear surgery.

Fast And Simple Automatic 3D Ultrasound Probe Calibration Based On 3D Printed Phantom And An Untracked Marker

Tracking the pose of an ultrasound (US) probe is essential for an intraoperative US-based navigation system. The tracking requires mounting a marker on the US probe and calibrating the probe. The goal of the US probe calibration is to determine the rigid transformation between the coordinate system (CS) of the image and the CS of the marker mounted on the probe. We present a fast and automatic calibration method based on a 3D printed phantom and an untracked marker for three-dimensional (3D) US probe calibration. To simplify the conventional calibration procedures using and tracking at least two markers, we used only one marker and did not track it in the whole calibration process. Our automatic calibration method is fast, simple and does not require any experience from the user. The performance of our calibration method was evaluated by point reconstruction tests. The root mean square (RMS) of the point reconstruction errors was 1.39 mm.

Design and evaluation of an actuated knee implant for postoperative ligament imbalance correction

In Total Knee Arthroplasty (TKA), the collateral ligament tensioning stage cannot be standardised for all patients and relies heavily on the surgeon's experience and perception. Intraoperative inaccuracies are practically unavoidable and may give rise to severe postoperative complications, leading to the need for revision surgery already a few years after primary TKA. This work proposes a novel instrumented tibial component able to detect collateral ligament laxity conditions right after primary TKA and, if needed, to compensate for them in the postoperative period. A miniaturised actuation system, designed to be embedded in the tibial baseplate, was initially evaluated by means of 3D simulations and then fabricated as a full-scale prototype. Stability and force sensors tests carried out on a knee simulator allowed to assess the effectiveness of the proposed design under normal working conditions and provided valuable insights for future work and improvements.

Enhanced position-force tracking of time-delayed teleoperation for robotic-assisted surgery

The advance of minimally invasive surgery has been empowered by new medical/surgical robotic systems towards achieving less invasiveness, smaller or even no scars. Wireless communication possesses great potential to be utilized in miniaturized surgical robotic system. However time delay is inevitably introduced in the control loop which causes stability issues for robotic-assisted surgeries. Wave variable based teleoperation structure provides stable force reflecting teleoperation performance but with both position and force tracking performance compromised due to conservative passivity condition. Recently, we proposed a new wave variable compensated structure to improve position and force tracking performance together with energy reservoir based regulators for stability purpose. In this paper, different energy reservoir based regulators are proposed with consideration of passivity of master and slave system to avoid uncertain compensated wave variables. Experiments are designed to evaluate the performance of proposed structure in comparison with traditional wave variable structure. Quantitative analyses of the obtained results justify the efficiency of proposed method.

Motion prediction using dual Kalman filter for robust beating heart tracking

A novel prediction method for robust beating heart tracking is proposed. The dual time-varying Fourier series is used to model the heart motion. The frequency parameters and Fourier coefficients in the model are estimated respectively by using a dual Kalman filter scheme. The instantaneous frequencies of breathing and heartbeat motion are measured online from the 3D trajectory of the point of interest using an orthogonal decomposition algorithm. The proposed method is evaluated based on both the simulated signals and the real motion signals, which are measured from the videos recorded using the da Vinci surgical system.

Unsupervised Trajectory Segmentation for Surgical Gesture Recognition in Robotic Training

Dexterity and procedural knowledge are two critical skills that surgeons need to master to perform accurate and safe surgical interventions. However, current training systems do not allow us to provide an in-depth analysis of surgical gestures to precisely assess these skills. Our objective is to develop a method for the automatic and quantitative assessment of surgical gestures. To reach this goal, we propose a new unsupervised algorithm that can automatically segment kinematic data from robotic training sessions. Without relying on any prior information or model, this algorithm detects critical points in the kinematic data that define relevant spatio-temporal segments. Based on the association of these segments, we obtain an accurate recognition of the gestures involved in the surgical training task. We, then, perform an advanced analysis and assess our algorithm using datasets recorded during real expert training sessions. After comparing our approach with the manual annotations of the surgical gestures, we observe 97.4% accuracy for the learning purpose and an average matching score of 81.9% for the fully automated gesture recognition process. Our results show that trainees workflow can be followed and surgical gestures may be automatically evaluated according to an expert database. This approach tends toward improving training efficiency by minimizing the learning curve.

Using rotation for steerable needle detection in 3D color-Doppler ultrasound images

This paper demonstrates a new way to detect needles in 3D color-Doppler volumes of biological tissues. It uses rotation to generate vibrations of a needle using an existing robotic brachytherapy system. The results of our detection for color-Doppler and B-Mode ultrasound are compared to a needle location reference given by robot odometry and robot ultrasound calibration. Average errors between detection and reference are 5.8 mm on needle tip for B-Mode images and 2.17 mm for color-Doppler images. These results show that color-Doppler imaging leads to more robust needle detection in noisy environment with poor needle visibility or when needle interacts with other objects.

Scaled position-force tracking for wireless teleoperation of miniaturized surgical robotic system

Miniaturized surgical robotic system presents promising trend for reducing invasiveness during operation. However, cables used for power and communication may affect its performance. In this paper we chose Zigbee wireless communication as a means to replace communication cables for miniaturized surgical robot. Nevertheless, time delay caused by wireless communication presents a new challenge to performance and stability of the teleoperation system. We proposed a bilateral wireless teleoperation architecture taking into consideration of the effect of position-force scaling between operator and slave. Optimal position-force tracking performance is obtained and the overall system is shown to be passive with a simple condition on the scaling factors satisfied. Simulation studies verify the efficiency of the proposed scaled wireless teleoperation scheme.

Synthesis of optimal electrical stimulation patterns for functional motion restoration: applied to spinal cord-injured patients

We investigated the synthesis of electrical stimulation patterns for functional movement restoration in human paralyzed limbs. We considered the knee joint system, co-activated by the stimulated quadriceps and hamstring muscles. This synthesis is based on optimized functional electrical stimulation (FES) patterns to minimize muscular energy consumption and movement efficiency criteria. This two-part work includes a multi-scale physiological muscle model, based on Huxley's formulation. In the simulation, three synthesis strategies were investigated and compared in terms of muscular energy consumption and co-contraction levels. In the experimental validation, the synthesized FES patterns were carried out on the quadriceps-knee joint system of four complete spinal cord injured subjects. Surface stimulation was applied to all subjects, except for one FES-implanted subject who received neural stimulation. In each experimental validation, the model was adapted to the subject through a parameter identification procedure. Simulation results were successful and showed high co-contraction levels when reference trajectories were tracked. Experimental validation results were encouraging, as the desired and measured trajectories showed good agreement, with an 8.4 % rms error in a subject without substantial time-varying behavior. We updated the maximal isometric force in the model to account for time-varying behavior, which improved the average rms errors from 31.4 to 13.9 % for all subjects.

Viscoelastic model based force control for soft tissue interaction and its application in physiological motion compensation

Controlling the interaction between robots and living soft tissues has become an important issue as the number of robotic systems inside the operating room increases. Many researches have been done on force control to help surgeons during medical procedures, such as physiological motion compensation and tele-operation systems with haptic feedback. In order to increase the performance of such controllers, this work presents a novel force control scheme using Active Observer (AOB) based on a viscoelastic interaction model. The control scheme has shown to be stable through theoretical analysis and its performance was evaluated by in vitro experiments. In order to evaluate how the force control scheme behaves under the presence of physiological motion, experiments considering breathing and beating heart disturbances are presented. The proposed control scheme presented a stable behavior in both static and moving environment. The viscoelastic AOB presented a compensation ratio of 87% for the breathing motion and 79% for the beating heart motion.

On the use of fixed-intensity functional electrical stimulation for attenuating essential tremor

A great proportion of essential tremor (ET) patients have not so far been able to receive functional benefits from traditional therapies. In this regard, the use of functional electrical stimulation (FES) has been proposed for reducing tremor amplitude by stimulating muscles in antiphase with respect to the trembling motion. Although some studies have reported success in terms of tremor attenuation, drawbacks still exist that prevent the method from being used in real-life applications. In this article, we explore an alternative approach: a strategy based on the hypothesis that FES-induced constant muscle contraction may provide functional benefit for tremor patients. To evaluate the proposed strategy, experiments were conducted in which stimulation was intermittently turned on and off while the subjects performed a static motor task. The results of the proposed experimental protocol indicate that tremor attenuation using this strategy is feasible, as consistent tremor attenuation levels were obtained in eight out of 10 ET patients. Nonetheless, tremor reduction was not instantaneous for all successful trials, indicating that prior training with FES may improve the overall response. Furthermore, although simpler assistive devices may potentially be designed based on this technique, some experimental difficulties still exist, which suggests that further studies are necessary.

A miniaturised actuation system embedded in an instrumented knee implant for postoperative ligament imbalance correction

During Total Knee Arthroplasty surgery, the orthopaedic surgeon has to set up proper balance conditions for the two lateral ligaments of the knee. Such ligament tensioning procedure is performed manually and mainly depends on the surgeon's experience. Unfortunately, inaccuracies are unavoidable and may give rise to serious postoperative complications. In the worst-case scenario, the only solution to this problem is represented by revision surgery. In order to cope with this problem, this work proposes a novel instrumented tibial component able to detect knee imbalance conditions in the postoperative period. A miniaturised actuation system embedded in the tibial baseplate allows to restore optimal balance conditions without resorting to revision surgery.

Innovative endoscopic sino-nasal and anterior skull base robotics

PURPOSE

Design a compact, ergonomic, and safe endoscope positioner dedicated to the sino-nasal tract, and the anterior and middle-stage skull base.

METHODS

A motion and force analysis of the surgeon's movement was performed on cadaver heads to gather objective data for specification purposes. An experimental comparative study was then performed with three different kinematics, again on cadaver heads, in order to define the best architecture satisfying the motion and force requirements.

RESULTS

We quantified the maximal forces applied on the endoscope when traversing the sino-nasal tract in order to evaluate the forces that the robot should be able to overcome. We also quantified the minimal forces that should not be exceeded in order to avoid damaging vital structures. We showed that the entrance point of the endoscope into the nostril could not be considered, as in laparoscopic surgery, as a fixed point but rather as a fixed region whose location and dimensions depend on the targeted sinus.

CONCLUSION

From the safety and ergonomic points of view, the best solution would be a co-manipulated standard 6-degree of freedom robot to which is attached a gimbal-like passive remote manipulator holding the endoscope.

Real-time control and evaluation of a teleoperated miniature arm for Single Port Laparoscopy

This paper presents the control architecture and the first performance evaluation results of a novel and highly-dexterous 18 degrees of freedom (DOF) miniature master/slave teleoperated robotic system called SPRINT (Single-Port la-paRoscopy bimaNual roboT). The system was evaluated in terms of positioning accuracy, repeatability, tracking error during local teleoperation and end-effector payload. Moreover, it was experimentally verified that the control architecture is real-time compliant at an operating frequency of 1 kHz and it is also reliable in terms of safety. The architecture accounts for cases when the robot is lead through singularities, and includes other safety mechanisms, such as supervision tasks and watchdog timers. Peliminary tests that were performed by surgeons in-vitro suggest that the SPRINT robot, along with its real-time control architecture, could become in the near future a reliable system in the field of Single Port Laparoscopy.

3D force control for robotic-assisted beating heart surgery based on viscoelastic tissue model

Current cardiac surgery faces the challenging problem of heart beating motion even with the help of mechanical stabilizer which makes delicate operation on the heart surface difficult. Motion compensation methods for robotic-assisted beating heart surgery have been proposed recently in literature, but research on force control for such kind of surgery has hardly been reported. Moreover, the viscoelasticity property of the interaction between organ tissue and robotic instrument further complicates the force control design which is much easier in other applications by assuming the interaction model to be elastic (industry, stiff object manipulation, etc.). In this work, we present a three-dimensional force control method for robotic-assisted beating heart surgery taking into consideration of the viscoelastic interaction property. Performance studies based on our D2M2 robot and 3D heart beating motion information obtained through Da Vinci™ system are provided.

Multiscale modeling of skeletal muscle properties and experimental validations in isometric conditions

In this article, we describe an approach to model the electromechanical behavior of the skeletal muscle based on the Huxley formulation. We propose a model that complies with a well established macroscopic behavior of striated muscles where force-length, force-velocity, and Mirsky-Parmley properties are taken into account. These properties are introduced at the microscopic scale and related to a tentative explanation of the phenomena. The method used integrates behavior ranging from the microscopic to the macroscopic scale, and allows the computation of the dynamics of the output force and stiffness controlled by EMG or stimulation parameters. The model can thus be used to simulate and carry out research to develop control strategies using electrical stimulation in the context of rehabilitation. Finally, through animal experiments, we estimated model parameters using a Sigma Point Kalman Filtering technique and dedicated experimental protocols in isometric conditions and demonstrated that the model can accurately simulate individual variations and thus take into account subject dependent behavior.

Joint angle estimation in rehabilitation with inertial sensors and its integration with Kinect

In this paper, we explore the combined use of inertial sensors and the Kinect for applications on rehabilitation robotics and assistive devices. In view of the deficiencies of each individual system, a new method based on Kalman filtering was developed in order to perform online calibration of sensor errors automatically whenever measurements from Kinect are available. The method was evaluated on experiments involving healthy subjects performing multiple DOF tasks.

Haptic feedback control in medical robots through fractional viscoelastic tissue model

In this paper, we discuss the design of an adaptive control system for robot-assisted surgery with haptic feedback. Through a haptic device, the surgeon teleoperates the medical instrument in free space, fixed on a remote robot or in contact. In free space, the surgeon feels the motion of the robot. In the present paper, we evaluated the performance of the controller on viscoelastic tissue, modeled by a fractional derivative equation. In addition, we propose a novel controller using an integer formalization process that is suitable for these tissue properties. The simulation results suggested that performance, in terms of force control and telepresence, became poorer when the conventional controller, which was designed for elastic target object, was applied to the viscoelastic tissues. In contrast, the results suggested that our proposed controller maintained its performance on the viscoelastic tissues.

Robust 3D tracking for robotic-assisted beating heart surgery

The past decades have witnessed the notable development of minimally invasive surgery (MIS). The benefits of this modality of surgery for patients are numerous, shortening convalescence, reducing trauma and surgery costs. In this context, robotic assistance aims to make the surgical act more intuitive and safer. In the domain of cardiac MIS, heartbeat and respiration represent two important sources of disturbances. Even though miniaturized versions of heart stabilizers have been conceived for the MIS scenario, residual motion is still considerable and has to be manually canceled by the surgeon. Our work focuses on computer vision techniques for estimating the 3D motion of the heart relying solely on natural structures on the heart surface for active compensation of physiological motions. We have developed in [2] a visual tracking method for estimating the 3D deformation of a region of interest on the heart surface based on the visual feedback of a stereo endoscope. The method is robust to illumination variations and large tissue deformations (Fig. 1).

EMG-based neuromuscular modeling with full physiological dynamics and its comparison with modified Hill model

EMG-based muscle model has many applications in human-machine interface and rehabilitation robotics. For the muscular force estimation, so-called Hill-type model has been used in most of the cases. It has already shown its promising performance, however it is known as a phenomenological model considering only macroscopic physiology. In this paper, we discuss EMG-force estimation with the full physiology based muscle model in voluntary contraction. In addition to Hill macroscopic representation, a microscopic physiology description as stated by Huxley and Zahalak is integrated. It has significant meaning to realize the same kind of EMG-force estimation with multiscale physiology based model not with a phenomenological Hill model, because it brings the understanding of the internal biophysical dynamics and new insights about neuromuscular activations.

Identification and validation of FES physiological musculoskeletal model in paraplegic subjects

The knowledge and prediction of the behavior of electrically activated muscles are important requisites for the movement restoration by FES in spinal cord injured subjects. The whole parameter's identification of a physiological musculoskeletal model for FES is investigated in this work. The model represents the knee and its associated quadriceps muscle. The identification protocol is noninvasive and based on the in-vivo experiments on paraplegic subjects. The isometric and nonisometric data was obtained by stimulating the quadriceps muscles of 3 paraplegic subjects through surface electrodes. A cross validation has been carried out using nonisometric data set. The normalized RMS errors between the identified model and the measured knee response are presented for each subject.

Filtering of intended motion for real-time tremor compensation in human upper limb using surface electromyography

The recorded motion from (pathological) tremor patient may consist of the involuntary tremulous component and the intended motion. These two components have to be separated so that the actuation part will be able to suppress only the tremor. This paper proposes an algorithm to remove the intended motion by using an extended Kalman filter with the help of adaptive high-pass filter. The effectiveness of the algorithm is also shown in the presence of stimulation artifacts. It is part of the active pathological tremor compensation project for human upper limb.

Three-dimensional Motion Tracking for Beating Heart Surgery Using a Thin-plate Spline Deformable Model

Minimally invasive cardiac surgery offers important benefits for the patient but it also imposes several challenges for the surgeon. Robotic assistance has been proposed to overcome many of the difficulties inherent to the minimally invasive procedure, but so far no solutions for compensating physiological motion are present in the existing surgical robotic platforms. In beating heart surgery, cardiac and respiratory motions are important sources of disturbance, hindering the surgeon’s gestures and limiting the types of procedures that can be performed in a minimally invasive fashion. In this context, computer vision techniques can be used for retrieving the heart motion for active motion stabilization, which improves the precision and repeatability of the surgical gestures. However, efficient tracking of the heart surface is a challenging problem due to the heart surface characteristics, large deformations and the complex illumination conditions. In this article, we present an efficient method for active cancellation of cardiac motion where we combine an efficient algorithm for 3D tracking of the heart surface based on a thin-plate spline deformable model and an illumination compensation algorithm able to cope with arbitrary illumination changes. The proposed method has two novelties: the thin-plate spline model for representing the heart surface deformations and an efficient parametrization for 3D tracking of the beating heart using stereo images from a calibrated stereo endoscope. The proposed tracking method has been evaluated offline on in vivo images acquired by a DaVinci surgical robotic platform.

Online pathological tremor characterization using extended Kalman filtering

This paper describes different algorithms that perform online pathological tremor characterization in terms of acceleration. Two distinct parametricmodels are used, an Auto-Regressive (AR) model and an harmonic model. Both models are recursively estimated with Extended Kalman Filters (EKFs). Experimental data was obtained with low cost sensors and the results are compared in terms of spectrogram estimation and prediction performance.

A neuromusculoskeletal model exploring peripheral mechanism of tremor

This paper studies the peripheral mechanism contributing to the tremor of human body. It is known that the reflex loops in peripheral nervous system have significant influences on the tremor. A neuromusculoskeletal model with several reflex loops is developed to explore the origin of tremor. The muscle model is developed based on a Hill-type muscle model. The feedback loops include the spindle organ, Golgi tendon organ and Renshaw cell. Their effects are investigated quantitatively in detail. Some results are in accordance with the previous research. Meanwhile, some new findings are proposed according to the simulation study.

Some control-related issues in mini-robotics for endoluminal surgery

This paper introduces some issues related to the development of robotics for endoluminal surgery from control point of view. Endoluminal surgery are incisionless procedures performed through natural orifices within the natural pathways. New devices are then required to achieve these new surgical procedures. Besides the development of new devices, control issues arise in both technological and theoretical aspects. The paper presents some of them and we propose a teleoperation architecture that has already been tested for needle insertion that could be used for teleoperated endoluminal surgery especially for instance for biopsies or anastomoses.

Efficient tracking of the heart using texture

Performing motion tracking in real-time is an old and recurrent problem in Computer Vision. It has been addressed through a large set of approaches [17], [9], [1], but achieving a high level of robustness is still a challenge, especially with low definition input. In the considered application, tracking the heart motion in endoscopic beating heart sequences, the sensitivity of existing algorithms to visual artifacts and variations in illumination is an issue that calls for improvements. In the prospect of developing a motion compensation architecture for robotically assisted beating heart surgery, we address the problem of visual information retrieval by proposing a new Composite Tracking Algorithm using both template matching and texture analysis. As we will show in this paper, the use of texture characterization of the heart surface improves the overall precision and robustness, in comparison with other prior approaches.

Ultrasound Image-Based Visual Servoing of a Surgical Instrument Through Nonlinear Model Predictive Control

Ultrasound image-guided interventions are widespread in surgery because of the non-invasive character of the procedures. However, hand/eye synchronization is relatively difficult for a surgeon. Ultrasound image-based visual servoing is one way to perform this kind of surgery. In this work, the control of instrument motion based on ultrasound images through nonlinear model predictive control is investigated. This new scheme ensures the convergence of the instrument to the desired position and also offers the possibility of satisfying constraints such as joint limits, actuator saturation and visibility preserving. This paper describes the proposed controller. The efficiency and the robustness of the proposed solution to control a six degree-of-freedom mechanical system is first illustrated by simulation. Experiments on a Mitsubishi PA10 robot highlight the efficiency of the vision control scheme to handle constraints of ultrasound image-based visual servoing.