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    Special Issue on Advanced Technologies for Medical Robotics
    Integrated Hydraulic-Driven Wearable Robot for Knee Assistance
    ZHAO Yafei (赵亚飞), HUANG Chaoyi (黄超逸), ZOU Yuging(邹玉莹), ZOUKehan(邹可涵), zoU Xiaogang(邹笑阳), XUE .Jiaqi(薛嘉琦), LI Xiaoting(李晓婷), KOH Keng Huat, WANG Xiaojun(王小军), LAI Wai Chiu King(赖伟超), HU Yong(胡勇), XI Ning(席宁), WANG Zheng(王峥)
    2023, 28 (3):  289-295.  doi: 10.1007/s12204-023-2602-2
    Abstract ( 439 )   PDF (1156KB) ( 164 )  
    Age-related diseases can lead to knee joint misfunction, making knee assistance necessary through the use of robotic wearable braces. However, existing wearable robots face challenges in force transmission and human motion adaptation, particularly among the elderly. Although soft actuators have been used in wearable robots, achieving rapid response and motion control while maintaining portability remains challenging. To address these issues, we propose a soft-robotic knee brace system integrated with multiple sensors and a direct-drive hydraulic actuation system. This approach allows for controlled and rapid force output on the portable hydraulic system. The multi-sensor feedback structure enables the robotic system to collaborate with the human body through human physiological signal and body motion information. The human user tests demonstrate that the knee robot provides assistive torques to the knee joint by being triggered by the electromyography signal and under human motion control.
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    Novel Concentric Tube Robot Based on Double-Threaded Helical Gear Tube
    CHEN Weichi(陈韦池), LIU Haocheng(刘浩城), LI Zijian(李子建), GUO Jing, (郭靖), ZHAI Zhenkun(翟振坤), MENG Wei(孟伟)
    2023, 28 (3):  296-306.  doi: 10.1007/s12204-023-2595-x
    Abstract ( 325 )   PDF (2087KB) ( 83 )  
    Nasopharyngeal carcinoma is a malignant tumor originating from the nasal mucosa. It is a malignant tumor of the head and neck. Concentric tube robot (CTR), as it can form a complicated shape and access hardto-reach lesions, is often used in minimally invasive surgeries. However, some CTRs are bulky because of their transmission design. In this paper, a light CTR based on double-threaded helical gear tube is proposed. Such a CTR is less cumbersome than the traditional CTR as its actuation unit is compact and miniaturized. The mapping relationship between the gear tube attitude and motor output angle is obtained by kinematic analysis. The precision, stability, and repeatability of the driving mechanism are tested. The experimental results show that the positioning error in the translation test is less than 0.3 mm, the rolling angle error in the stability test is less than 0.6?, and the error in the translation repeatability test is less than 0.005 mm. Finally, a tip-targeting test is performed using the new CTR, which verifies the feasibility of the CTR for surgeries.
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    Enhancement of Pinching Grasping Robustness Using a Multi-Structure Soft Gripper
    LI Linlin (李林霖), GAO Feiyang (高飞扬), ZHENG Xiongfei(郑雄飞), ZHANG Liming(张黎明), LI Shijie (李世杰), WANG Heran(王赫然)
    2023, 28 (3):  307-311.  doi: 10.1007/s12204-022-2508-4
    Abstract ( 244 )   PDF (2071KB) ( 65 )  
    Recently, soft grippers have garnered considerable interest in various fields, such as medical rehabilitation, due to their high compliance. However, the traditional PneuNet only reliably grasps medium and large objects via enveloping grasping (EG), and cannot realize pinching grasping (PG) to stably grasp small and thin objects as EG requires a large bending angle whereas PG requires a much smaller one. Therefore, we proposed a multi-structure soft gripper (MSSG) with only one vent per finger which combines the PneuNet in the proximal segment with the normal soft pneumatic actuator (NSPA) in the distal segment, allowing PG to be realized without a loss in EG and enhancing the robustness of PG due to the height difference between the distal and proximal segments. Grasping was characterized on the basis of the stability (finger bending angle describes) and robustness (pull-out force describes), and the bending angle and pull-out force of MSSG were analyzed using the finite element method. Furthermore, the grasping performance was validated using experiments, and the results demonstrated that the MSSG with one vent per finger was able to realize PG without a loss in EG and effectively enhance the PG robustness.
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    Shape Sensing for Single-Port Continuum Surgical Robot Using Few Multicore Fiber Bragg Grating Sensors
    LI Dingjia1,2,3,4(黎定佳),WANG Chongang1,2,3(王重阳),GUO Wei5(郭伟),WANG Zhidong6(王志东),ZHANG Zhongtao5(张忠涛),LIU Hao1,2,3*(刘浩)
    2023, 28 (3):  312-322.  doi: 10.1007/s12204-023-2579-x
    Abstract ( 326 )   PDF (2606KB) ( 60 )  
    We proposed a method for shape sensing using a few multicore fiber Bragg grating (FBG) sensors in a single-port continuum surgical robot (CSR). The traditional method of utilizing a forward kinematic model to calculate the shape of a single-port CSR is limited by the accuracy of the model. If FBG sensors are used for shape sensing, their accuracy will be affected by their number, especially in long and flexible CSRs. A fusion method based on an extended Kalman filter (EKF) was proposed to solve this problem. Shape reconstruction was performed using the CSR forward kinematic model and FBG sensors, and the two results were fused using an EKF. The CSR reconstruction method adopted the incremental form of the forward kinematic model, while the FBG sensor method adopted the discrete arc-segment assumption method. The fusion method can eliminate the inaccuracy of the kinematic model and obtain more accurate shape reconstruction results using only a small number of FBG sensors. We validated our algorithm through experiments on multiple bending shapes under different load conditions. The results show that our method significantly outperformed the traditional methods in terms of robustness and effectiveness.
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    Visual Positioning of Nasal Swab Robot Based on Hierarchical Decision
    LI Guozhia a(李国志),ZOU Shuizhong b*(邹水中),DING Shuacue a(丁数学)
    2023, 28 (3):  323-329.  doi: 10.1007/s12204-023-2581-3
    Abstract ( 258 )   PDF (743KB) ( 47 )  
    This study focuses on a robot vision localization method for coping with the operational task of automatic nasal swab sampling. The application is important in the detection and epidemic prevention of Corona Virus Disease 2019 (COVID-19) to alleviate the large-scale negative impact of individuals suffering from pneumonia owing to COVID-19. In this method, the idea of a hierarchical decision network is used to consider the strong infectious characteristics of the COVID-19, which is followed by processing the robot behavior constraint condition. The visual navigation and positioning method using a single-arm robot for sampling is also planned, which considers the operation characteristics of medical staff. In the decision network, the risk factor for potential contact infection caused by swab sampling operations is established to avoid the spread among personnel. A robot visual servo control with artificial intelligence characteristics is developed to achieve a stable and safe nasal swab sampling operation. Experiments demonstrate that the proposed method can achieve good vision positioning for the robots and provide technical support for managing new major public health situations.
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    Real-Time Slice-to-Volume Registration-Based Autonomous Navigation for Robot-Assisted Thyroid Biopsy
    LI Jian1 (李坚),WANG Xingchao1 (王星超),ZHONG Min2 (钟敏),ZHENG Jian2(郑剑),SUN Zhenglong1*(孙正隆)
    2023, 28 (3):  330-338.  doi: 10.1007/s12204-023-2606-y
    Abstract ( 215 )   PDF (1034KB) ( 35 )  
    With advancements in medical imaging and robotic technology, the idea of fully autonomous diagnosis and treatment has become appealing, from ethereal to tangible. Owing to its characteristics of non-invasiveness, non-radiation, and fast imaging speed, ultrasonography has been increasingly used in clinical practice, such as in obstetrics, gynecology, and surgical puncture. In this paper, we propose a real-time image-based visual servo control scheme using a hybrid slice-to-volume registration method. In this manner, the robot can autonomously locate the ultrasound probe to the desired posture according to preoperational planning, even in the presence of disturbances. The experiments are designed and conducted using a thyroid biopsy phantom model. The results show that the proposed scheme can achieve a refresh rate of up to 30 Hz and a tracking accuracy of (0.52±0.65) mm.
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    On Flexible Trajectory Description for Effective Rigid Body Motion Reproduction and Recognition
    YANG Jian xin(杨健鑫),GUo Yao*(郭遥)
    2023, 28 (3):  339-347.  doi: 10.1007/s12204-023-2604-0
    Abstract ( 169 )   PDF (1121KB) ( 30 )  
    Recognizing and reproducing spatiotemporal motions are necessary when analyzing behaviors and movements during human-robot interaction. Rigid body motion trajectories are proven as compact and informative clues in characterizing motions. A flexible dual square-root function (DSRF) descriptor for representing rigid body motion trajectories, which can offer robustness in the description over raw data, was proposed in our previous study. However, this study focuses on exploring the application of the DSRF descriptor for effective backward motion reproduction and motion recognition. Specifically, two DSRF-based reproduction methods are initially proposed, including the recursive reconstruction and online optimization. New trajectories with novel situations and contextual information can be reproduced from a single demonstration while preserving the similarities with the original demonstration. Furthermore, motion recognition based on DSRF descriptor can be achieved by employing a template matching method. Finally, the experimental results demonstrate the effectiveness of the proposed method for rigid body motion reproduction and recognition.
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    Input-Constrained Hybrid Control of a Hyper-Redundant Mobile Medical Manipulator
    ZHANG Kaibo1(张凯波),CHEN Li1*(陈丽),DONG Qi2(董琦)
    2023, 28 (3):  348-359.  doi: 10.1007/s12204-023-2580-4
    Abstract ( 243 )   PDF (909KB) ( 33 )  
    To reduce the risk of infection in medical personnel working in infectious-disease areas, we proposed a hyper-redundant mobile medical manipulator (HRMMM) to perform contact tasks in place of healthcare workers. A kinematics-based tracking algorithm was designed to obtain highly accurate pose tracking. A kinematic model of the HRMMM was established and its global Jacobian matrix was deduced. An expression of the tracking error based on the Rodrigues rotation formula was designed, and the relationship between tracking errors and gripper velocities was derived to ensure accurate object tracking. Considering the input constraints of the physical system, a joint-constraint model of the HRMMM was established, and the variable-substitution method was used to transform asymmetric constraints to symmetric constraints. All constraints were normalized by dividing by their maximum values. A hybrid controller based on pseudo-inverse (PI) and quadratic programming (QP) was designed to satisfy the real-time motion-control requirements in medical events. The PI method was used when there was no input saturation, and the QP method was used when saturation occurred. A quadratic performance index was designed to ensure smooth switching between PI and QP. The simulation results showed that the HRMMM could approach the target pose with a smooth motion trajectory, while meeting different types of input constraints.
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    Foreground Segmentation Network with Enhanced Attention
    JIANG Rui1*(姜﹐锐),ZHU Ruiriang1(朱瑞祥),CAI Xiaocui1(蔡萧萃),SU Hu2(苏虎)
    2023, 28 (3):  360-369.  doi: 10.1007/s12204-023-2603-1
    Abstract ( 350 )   PDF (734KB) ( 47 )  
    Moving object segmentation (MOS) is one of the essential functions of the vision system of all robots,including medical robots. Deep learning-based MOS methods, especially deep end-to-end MOS methods, are actively investigated in this field. Foreground segmentation networks (FgSegNets) are representative deep end-to-end MOS methods proposed recently. This study explores a new mechanism to improve the spatial feature learning capability of FgSegNets with relatively few brought parameters. Specifically, we propose an enhanced attention (EA) module, a parallel connection of an attention module and a lightweight enhancement module, with sequential attention and residual attention as special cases. We also propose integrating EA with FgSegNet v2 by taking the lightweight convolutional block attention module as the attention module and plugging EA module after the two Maxpooling layers of the encoder. The derived new model is named FgSegNet v2 EA. The ablation study verifies the effectiveness of the proposed EA module and integration strategy. The results on the CDnet2014 dataset, which depicts human activities and vehicles captured in different scenes, show that FgSegNet v2 EA outperforms FgSegNet v2 by 0.08% and 14.5% under the settings of scene dependent evaluation and scene independent evaluation, respectively, which indicates the positive effect of EA on improving spatial feature learning capability of FgSegNet v2.
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    Progress in Force-Sensing Techniques for Surgical Robots
    GAO Hongyan1,2(高红岩),AI Xiaojie1,2(艾孝杰),SUN Zhenglong3(孙正隆),CHEN Weidong1,2(陈卫东),GAO Anzhu1,2*(高安柱)
    2023, 28 (3):  370-381.  doi: 10.1007/s12204-023-2607-x
    Abstract ( 643 )   PDF (1017KB) ( 203 )  
    Force sensing is vital for situational awareness and safe interaction during minimally invasive surgery. Consequently, surgical robots with integrated force-sensing techniques ensure precise and safe operations. Over the past few decades, there has been considerable progress in force-sensing techniques for surgical robots. This review summarizes the existing electrically- and optically-based force sensors for surgical robots, including piezoresistive, piezoelectric, capacitive, intensity/phase-modulated, and fiber Bragg gratings. Their principles, applications, advantages, and limitations are also discussed. Finally, we summarize our conclusions regarding state-of-the-art force-sensing technologies for surgical robotics.
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    Development of Rehabilitation and Assistive Robots in China: Dilemmas and Solutions
    ZHAO Lingling1*(赵玲玲),GUO Yao2(郭遥)
    2023, 28 (3):  382-390.  doi: 10.1007/s12204-023-2596-9
    Abstract ( 357 )   PDF (367KB) ( 76 )  
    China is rapidly becoming an aging society, leading to a significant demand for chronic disease management and personalized healthcare. The development of rehabilitation and assistive robotics in China has gathered significant attention not only in research fields but also in industries. Such robots aim to either guide patients in completing therapeutic training or assist people with impaired functions in performing their daily activities. In the past decades, we have witnessed the advancement in rehabilitation and assistive robotics, with diverse mechanical designs, functionalities, and purposes. However, the construction of dedicated regulations and policies is relatively lagged compared with the flourishing development in research fields. Moreover, these kinds of robots are working or collaborating closely with human beings, bringing unprecedented considerations on ethical issues. This paper aims to provide an overview of major dilemmas in the development of rehabilitation and assistive robotics in China and propose several potential solutions.
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