A novel constrained tendon-driven serpentine manipulator

Abstract

In this paper, a novel constrained tendon-driven serpentine manipulator (CTSM) suited for minimally invasive surgery is presented. It comprises a flexible backbone, a set of controlling tendons and a constraint. In the CTSM not only the curvature of the bending section can be controlled but also the length. Specifically, the curvature is controlled by the tendons, and the length is controlled by a constraint tube, which is translational and is concentric with the flexible backbone. The kinematic model of the CTSM is developed based on the piecewise constant curvature assumption. An analysis shows that by introducing the translational constraint both the workspace and dexterity of the manipulator are improved. The stiffer the constraint the larger the workspace expansion and the smaller the dexterity enhancement. A prototype is developed and the experimental results validate the design idea and analysis.

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A preliminary study of force estimation based on surface EMG: Towards neuromechanically guided soft oral rehabilitation robot

Abstract

Surface electromyography (sEMG) signals have been extensively studied in the area of intention detection, force estimation and control of rehabilitation devices. Studies regarding sEMG based jaw muscle force estimation are necessary towards building intuitive neural-controlled soft oral rehabilitation robot (SORR). This paper presents a force estimation algorithm based on masseter muscle sEMG signals to be used in the control of a developed SORR. Experiments were conducted to collect masseter muscle sEMG signals and biting force from 10 healthy subjects. By using two different time-frequency analysis, signal features were extracted and then input to an empirically established second-order polynomial force estimator to get the estimated force. Comparison has been made regarding to the performance of the proposed feature extraction algorithms. The results obtained from both the algorithms represent a decent accuracy in force estimation, indicating high implementation feasibility in the application of the neural-controlled SORR.

Design of a Novel Flexible Endoscope-Cardioscope

Abstract

In this paper, we present a novel flexible endoscope which is well suited to minimally invasive cardiac surgery (MICS). It is named ‘the Cardioscope’. The Cardioscope is composed of a handle, a rigid shaft, a flexible section and the imaging system. The flexible section is composed of an elastic tube, a number of spacing discs, a constraint tube, and four tendons. Compared with other flexible endoscopes, the Cardioscope is much more dexterous. The maximum bending angle of the Cardioscope is 190°. Ex-vivo tests show that the cardioscope is well suited to (MICS), it provides the much larger scope of vision than rigid endoscopes and provides good manipulation inside the confined environment. In the test, the Cardioscope successfully explores the full heart through a single hole, which shows the design is promising. Despite it was designed for MICS, the Cardioscope can also be applied to other minimally invasive surgeries, such as laparoscopy, neurosurgery, transnasal and transoral surgery. Copyright © 2015 by ASME Country-Specific Mortality and Growth Failure in Infancy and Young Children and Association With Material Stature Use interactive graphics and maps to view and sort country-specific infant and early childhood mortality and growth failure data and their association with maternal

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Maker based shape tracking of a flexible serpentine manipulator

Abstract

With the advancement of minimally invasive surgery, there has been increasing interest from both industry and academia in developing flexible serpentine manipulators for surgical robotic systems. Due to internal friction and external disturbance when interacting with complex environment, position and shape of the flexile manipulator cannot be estimated solely by kinematic models. Hence, shape tracking of such manipulator is crucial to close the control loop and to study the robot models. In this paper, we propose a marker-based method with stereo vision for tracking the shape of the flexible manipulator by extracting position information of each independent joint. The performance of the algorithm was validated by experiments and was compared with that of electromagnetics tracking method.

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Real-Time Shape Estimation for Wire-Driven Flexible Robots with Multiple Bending Sections Based on Quadratic Bezier Curves

Abstract

The wire-driven flexible robot with multiple bending sections is an efficient approach for the minimally invasive surgery and diagnosis. It can function properly in the complicated and restrained environment. One drawback of this technology is that the real time positional and shape information cannot be well estimated. In order to settle this limitation, we proposed a novel shape estimation method for a wire-driven flexible robot with multiple bending sections in this paper. Each bending section can be controlled independently to deform as an arc with different curvature. This method is based on the positional and directional information of limited specific joints on the robot, which can be estimated with an effective positioning method, such as electromagnetic tracking method. The number and position of these specific joints are only determined by the number of sections. Based on the positional and directional information, as well as the curve length information, the shape reconstruction algorithm can be carried out by fitting multiple quadratic B´ezier curves. Real time shape sensing platform is built to verify the proposed method. Experimental results show that the method works well and the mean position error is 1.7mm.

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Target Recognition in Synthetic Aperture Radar Images via Non-negative Matrix Factorisation

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This study proposes a novel non-negative matrix factorisation (NMF) variant L1/2-NMF after visualisation and analysis of the process of target recognition via NMF for synthetic aperture radar (SAR) images. NMF has been applied to obtain pattern feature in SAR images. This study considers the intrinsic character and the physical meaning of NMF feature when applied for SAR automatic target recognition. At the base of obtaining the linear relationship between the sample to be recognised and the train samples, the whole recognition process is detailed and vividly visualised. Meanwhile, lots of researches have been done to improve NMF methods by enforcing sparse constraint with L1-norm, such as non-negative sparse coding (NNSC), local NMF and sparse NMF. Compared with L1-norm, L1/2-norm has been shown to have a more natural sparseness. In this study, a novel variant of NMF with L1/2 constraint, called L1/2-NMF is proposed, and is carried out a thorough study by applying it in SAR target recognition. Experimental results on MSTAR public database show that both the basis and coding matrices obtained by L1/2-NMF have higher sparseness than those obtained by NMF, NNSC and NMF with sparseness constraints (NMFsc). The recognition results demonstrate that the L1/2-NMF outperforms NNSC, NMFsc and non-smooth NMF.

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Kernel neighbor density with parallel computing mechanism for anomaly detection algorithm

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Anomaly detection is an important research direction in the field of data mining and industrial dataset preprocess. The paper proposed a kernel neighbor densitydefinition with parallel computing mechanism for anomaly detection algorithm. The kernel neighbor density formula calculates the density of points in high dimensional space. In our definition, we adopt the median operation because the breakdown point of the median is the largest possible. So thedefinition could be a very robust estimate of the data location, and parallel computing mechanism is introduced to improve the efficiency of algorithms. We use two real datasets and three different kernel functions to evaluate the performance of algorithms. The experiment results confirm that the presenteddefinition of kernel neighbor density improves the performance of algorithms and the Gaussian kernel function has the best effect

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Soft oral interventional rehabilitation robot based on low-profile soft pneumatic actuator

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Mandibular mobility plays a significant role in human daily lives, enabling food intake, respiration, speaking, and other oral activities. However, as for the patients suffering from mandibular mobility disorders, their mandible functions are deteriorated, which severely affects their quality of life. In this paper, we present a new solution to recover mandibular mobility: A soft oral rehabilitation robot (SORR), which is actuated by a novel type of soft pneumatic actuator (SPA). After identifying the biometrics of the human mandible, we illustrate the application-oriented design of the robot and the SPA. A static model of the SPA was established to predict its behavior and eligibility for the application. In the experimental characterization, we measured the elongation and force output of the SPA, and the detailed results are presented. The comparison and analysis of the results provide physical insight into the mechanisms of the SPA. As the first application of soft robot inside human body, this work enlightens profound application potentials of the silicone-based SPAs.

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