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Shaolong Kuang
Collaborative Innovation Center of Suzhou Nano Science and Technology, Suzhou 215000, China

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Journal article
Published: 24 May 2021 in Electronics
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This paper aims at realizing upper limb rehabilitation training by using an fNIRS-BCI system. This article mainly focuses on the analysis and research of the cerebral blood oxygen signal in the system, and gradually extends the analysis and recognition method of the movement intention in the cerebral blood oxygen signal to the actual brain-computer interface system. Fifty subjects completed four upper limb movement paradigms: Lifting-up, putting down, pulling back, and pushing forward. Then, their near-infrared data and movement trigger signals were collected. In terms of the recognition algorithm for detecting the initial intention of upper limb movements, gradient boosting tree (GBDT) and random forest (RF) were selected for classification experiments. Finally, RF classifier with better comprehensive indicators was selected as the final classification algorithm. The best offline recognition rate was 94.4% (151/160). The ReliefF algorithm based on distance measurement and the genetic algorithm proposed in the genetic theory were used to select features. In terms of upper limb motion state recognition algorithms, logistic regression (LR), support vector machine (SVM), naive Bayes (NB), and linear discriminant analysis (LDA) were selected for experiments. Kappa coefficient was used as the classification index to evaluate the performance of the classifier. Finally, SVM classification got the best performance, and the four-class recognition accuracy rate was 84.4%. The results show that RF and SVM can achieve high recognition accuracy in motion intentions and the upper limb rehabilitation system designed in this paper has great application significance.

ACS Style

Chunguang Li; Yongliang Xu; Liujin He; Yue Zhu; Shaolong Kuang; Lining Sun. Research on fNIRS Recognition Method of Upper Limb Movement Intention. Electronics 2021, 10, 1239 .

AMA Style

Chunguang Li, Yongliang Xu, Liujin He, Yue Zhu, Shaolong Kuang, Lining Sun. Research on fNIRS Recognition Method of Upper Limb Movement Intention. Electronics. 2021; 10 (11):1239.

Chicago/Turabian Style

Chunguang Li; Yongliang Xu; Liujin He; Yue Zhu; Shaolong Kuang; Lining Sun. 2021. "Research on fNIRS Recognition Method of Upper Limb Movement Intention." Electronics 10, no. 11: 1239.

Research article
Published: 01 July 2020 in Science Progress
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Topology optimization is a widely used lightweight design method for structural design of the collaborative robot. In this article, a topology optimization method for the robot lightweight design is proposed based on finite element analysis of the assembly so as to get the minimized weight and to avoid the stress analysis distortion phenomenon that compared the conventional topology optimization method by adding equivalent confining forces at the analyzed part’s boundary. For this method, the stress and deformation of the robot’s parts are calculated based on the finite element analysis of the assembly model. Then, the structure of the parts is redesigned with the goal of minimized mass and the constraint of maximum displacement of the robot’s end by topology optimization. The proposed method has the advantages of a better lightweight effect compared with the conventional one, which is demonstrated by a simple two-linkage robot lightweight design. Finally, the method is applied on a 5 degree of freedom upper-limb exoskeleton robot for lightweight design. Results show that there is a 10.4% reduction of the mass compared with the conventional method.

ACS Style

Liansen Sha; Andi Lin; Xinqiao Zhao; Shaolong Kuang. A topology optimization method of robot lightweight design based on the finite element model of assembly and its applications. Science Progress 2020, 103, 1 .

AMA Style

Liansen Sha, Andi Lin, Xinqiao Zhao, Shaolong Kuang. A topology optimization method of robot lightweight design based on the finite element model of assembly and its applications. Science Progress. 2020; 103 (3):1.

Chicago/Turabian Style

Liansen Sha; Andi Lin; Xinqiao Zhao; Shaolong Kuang. 2020. "A topology optimization method of robot lightweight design based on the finite element model of assembly and its applications." Science Progress 103, no. 3: 1.

Journal article
Published: 11 March 2020 in IEEE Access
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In chest and abdomen robotic radiosurgery, due to the motion delay of the robotic manipulator, the tumor position tracking process has a period of delay. This delay ultimately affects the accuracy of radiosurgery treatment. To address the influence of the delay in robotic radiosurgery, a Long-and-Short-Term Memory (LSTM) network as a deep Recurrent Neural Network (RNN) has been applied in a prediction network model for respiratory motion tracking in recent years. However, patients’ respiratory state may change in the process of treatment, which may influence the accuracy of prediction. Therefore, it is necessary to update the prediction network through additional data, such as the actual position of the tumor obtained by X-ray imaging. However, the LSTM network has a long update time, and it may not be able to complete the prediction model update in a cycle of X-ray acquisition. To solve this problem, a fast prediction model based on Bidirectional Gated Recurrent Unit (Bi-GRU), is proposed in this paper. This method can reduce the average updating time of the network model by 30%.

ACS Style

Shumei Yu; Jiateng Wang; Jinguo Liu; Rongchuan Sun; Shaolong Kuang; Lining Sun. Rapid Prediction of Respiratory Motion Based on Bidirectional Gated Recurrent Unit Network. IEEE Access 2020, 8, 49424 -49435.

AMA Style

Shumei Yu, Jiateng Wang, Jinguo Liu, Rongchuan Sun, Shaolong Kuang, Lining Sun. Rapid Prediction of Respiratory Motion Based on Bidirectional Gated Recurrent Unit Network. IEEE Access. 2020; 8 (99):49424-49435.

Chicago/Turabian Style

Shumei Yu; Jiateng Wang; Jinguo Liu; Rongchuan Sun; Shaolong Kuang; Lining Sun. 2020. "Rapid Prediction of Respiratory Motion Based on Bidirectional Gated Recurrent Unit Network." IEEE Access 8, no. 99: 49424-49435.

Original article
Published: 21 February 2020 in Medical & Biological Engineering & Computing
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Since more and more elderly people suffer from lower extremity movement problems, it is of great social significance to assist persons with motor dysfunction to walk independently again and reduce the burden on caregivers. The self-paced walking intention, which could increase the ability of self-control on the start and stop of motion, was studied by applying brain-computer interface (BCI) technology, a novel research field. The cerebral hemoglobin signal, which was obtained from 30 subjects by applying functional near-infrared spectroscopy (fNIRS) technology, was processed to detect self-paced walking intention in this paper. Teager-Kaiser energy was extracted at each sampling point for five sub-bands (0.0095~0.021 Hz, 0.021~0.052 Hz, 0.052~0.145 Hz, 0.145~0.6 Hz, and 0.6~2.0 Hz). Gradient boosting decision tree (GBDT) was then utilized to establish the detecting model in real-time. The proposed method had a good performance to detect the walking intention and passed the pseudo-online test with a true positive rate of 100% (80/80), a false positive rate of 2.91% (4822/165171), and a detection latency of 0.39 ± 1.06 s. GBDT method had an area under the curve value of 0.944 and was 0.125 (p < 0.001) higher than linear discriminant analysis (LDA). The results reflected that it is feasible to decode self-paced walking intention by applying fNIRS technology. This study lays a foundation for applying fNIRS-based BCI technology to control walking assistive devices practically. Graphical abstract Graphical representation of the detecting process for pseudo-online test. The lower figure is a partial enlargement of the upper figure. In the lower figure, the blue line represents the probability of walking predicted by GBDT without smoothing and the orange-red line represents the smoothed probability. The dark-red ellipse shows the effect of the smoothing-threshold method.

ACS Style

Chunguang Li; Jiacheng Xu; Yufei Zhu; Shaolong Kuang; Wei Qu; Lining Sun. Detecting self-paced walking intention based on fNIRS technology for the development of BCI. Medical & Biological Engineering & Computing 2020, 58, 933 -941.

AMA Style

Chunguang Li, Jiacheng Xu, Yufei Zhu, Shaolong Kuang, Wei Qu, Lining Sun. Detecting self-paced walking intention based on fNIRS technology for the development of BCI. Medical & Biological Engineering & Computing. 2020; 58 (5):933-941.

Chicago/Turabian Style

Chunguang Li; Jiacheng Xu; Yufei Zhu; Shaolong Kuang; Wei Qu; Lining Sun. 2020. "Detecting self-paced walking intention based on fNIRS technology for the development of BCI." Medical & Biological Engineering & Computing 58, no. 5: 933-941.

Journal article
Published: 17 February 2020 in IEEE Access
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ACS Style

Baiquan Su; Hao Yan; Liaoliao Liu; Shi Yu; Yida Hu; Gang Wang; Wei Yao; Jie Tang; Shaolong Kuang. A Position-Adjustable Multi-Point Synchronizing Biopsy Tool for Intratumor Heterogeneity: A Proof-of-Principle Study. IEEE Access 2020, 8, 34431 -34441.

AMA Style

Baiquan Su, Hao Yan, Liaoliao Liu, Shi Yu, Yida Hu, Gang Wang, Wei Yao, Jie Tang, Shaolong Kuang. A Position-Adjustable Multi-Point Synchronizing Biopsy Tool for Intratumor Heterogeneity: A Proof-of-Principle Study. IEEE Access. 2020; 8 ():34431-34441.

Chicago/Turabian Style

Baiquan Su; Hao Yan; Liaoliao Liu; Shi Yu; Yida Hu; Gang Wang; Wei Yao; Jie Tang; Shaolong Kuang. 2020. "A Position-Adjustable Multi-Point Synchronizing Biopsy Tool for Intratumor Heterogeneity: A Proof-of-Principle Study." IEEE Access 8, no. : 34431-34441.

Journal article
Published: 12 February 2020 in Applied Materials Today
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Liquid metal (LM) droplets made from gallium-based alloys exhibit excellent biomimetic locomotion and deformation capabilities under external stimulating fields and have presented potentials in a variety of applications. However, its application in robotics is presently hampered by limited maneuverability in two-dimensional (2D) space and weak cargo carrying capacity. Here, we propose a composite liquid metal droplet robot (LMDR) which appears as a LM droplet but exhibits an extraordinary actuating performance in 3D space. The LMDR is fabricated by assembling a hollow and spherical-shaped magnetic internal framework (IF) into a LM droplet, and the IF can be disassembled from the LM droplet with the application of an external magnetic field. The maneuver of the LMDR is realized using the interplay of electric and magnetic fields, and complex actuation especially jumping to avoid obstacles, climbing steep slopes, and rotating its body to the desired posture can be achieved. The hollow IF within the LMDR has a cargo carrying capacity and we demonstrate a proof-of-concept experiment to show the transportation and controlled release of a chemical indicator using the LMDR. More importantly, an in vitro targeted drug delivery and therapy trial to treat breast cancer cells (4T1) with a drug loaded LMDR is also successfully performed. The demonstrated capabilities of the LMDR present a promising potential in developing future targeted drug delivery and soft robotic systems with high controllability and multi-functionalities.

ACS Style

Fangxia Li; Jian Shu; Leran Zhang; Nailin Yang; Jie Xie; Xiangpeng Li; Liang Cheng; Shaolong Kuang; Shi-Yang Tang; Shiwu Zhang; Weihua Li; Lining Sun; Dong Sun. Liquid metal droplet robot. Applied Materials Today 2020, 19, 100597 .

AMA Style

Fangxia Li, Jian Shu, Leran Zhang, Nailin Yang, Jie Xie, Xiangpeng Li, Liang Cheng, Shaolong Kuang, Shi-Yang Tang, Shiwu Zhang, Weihua Li, Lining Sun, Dong Sun. Liquid metal droplet robot. Applied Materials Today. 2020; 19 ():100597.

Chicago/Turabian Style

Fangxia Li; Jian Shu; Leran Zhang; Nailin Yang; Jie Xie; Xiangpeng Li; Liang Cheng; Shaolong Kuang; Shi-Yang Tang; Shiwu Zhang; Weihua Li; Lining Sun; Dong Sun. 2020. "Liquid metal droplet robot." Applied Materials Today 19, no. : 100597.

Journal article
Published: 06 January 2020 in IEEE/ASME Transactions on Mechatronics
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As an emerging multifunctional material, Gallium based room temperature liquid metal has attracted a lot of attention for a variety of applications due to its mobility and deformability. However, controlling the motion of a liquid metal droplet accurately still remains unrevealed, which restricts its application in many fields. In this paper we propose a hybrid framework that would control the motion of a liquid metal droplet in a one-dimensional fluidic channel. A dynamic model of a liquid metal droplet immersed in the electrolyte when an electrical field is applied to each end of the channel is discussed first, followed by a setpoint controller designed to calculate the current input needed to drive the liquid metal droplet to its destination with vision feedback. To obtain the desired high-resolution current output, a fast and high-resolution current output power supply will be established by integrating a fast PID controller and a simple programmable DC power supply. The effectiveness of this proposed approach will be verified by controlling a liquid metal droplet so that it reaches its destination inside the PMMA channel. This proposed approach may lead to the development of tiny soft robots, or micro-fluidic systems that can be driven accurately by liquid metal droplets.

ACS Style

Jie Xie; Fangxia Li; Shaolong Kuang; Hao Yang; Xiangpeng Li; Shi-Yang Tang; Weihua Li; Shiwu Zhang. Modeling and Motion Control of a Liquid Metal Droplet in a Fluidic Channel. IEEE/ASME Transactions on Mechatronics 2020, 25, 942 -950.

AMA Style

Jie Xie, Fangxia Li, Shaolong Kuang, Hao Yang, Xiangpeng Li, Shi-Yang Tang, Weihua Li, Shiwu Zhang. Modeling and Motion Control of a Liquid Metal Droplet in a Fluidic Channel. IEEE/ASME Transactions on Mechatronics. 2020; 25 (2):942-950.

Chicago/Turabian Style

Jie Xie; Fangxia Li; Shaolong Kuang; Hao Yang; Xiangpeng Li; Shi-Yang Tang; Weihua Li; Shiwu Zhang. 2020. "Modeling and Motion Control of a Liquid Metal Droplet in a Fluidic Channel." IEEE/ASME Transactions on Mechatronics 25, no. 2: 942-950.

Journal article
Published: 19 September 2019 in IEEE Access
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Physical human-robot interaction(pHRI) is the most popular way to ensure the safety in robot surgery. Current research of pHRI in operation room focuses on the inside of the surgical area, which adapts virtual fixtures method for ensuring the safety of drag. But the safety problems caused by human error in the stage of dragging the robot from the outside surgical area to the inside surgical area are ignored. Therefore, a method of applying virtual fixtures to the outside of the surgical area is proposed to solve the safety issues during dragging stage outside surgical area. This method takes the kinematics model of human arm as the reference motion trajectory to construct the guided virtual fixtures, which is to restrict the robot movement in a defined area during the pHRI drag. This drag is based on admittance control method to improve safety and ensure flexibility. Experiment results show that the constructed guided virtual fixtures with the trajectory of the human arm model as the central axis, with radius 30mm, and restrict area 5mm can effectively limit the robot motion to a certain range. Simultaneously, the output speed of the robot in tangent direction of the central axis can well follow the change of the force applied by the doctor, and the output speed in the normal direction of the central axis can converge to zero stably at the pipeline boundary. Consequently, the purpose of improving the safety and flexibility of the surgical robot before surgical operation is realized.

ACS Style

Andi Lin; Yucun Tang; Minfeng Gan; Lixin Huang; Shaolong Kuang; Lining Sun. A Virtual Fixtures Control Method of Surgical Robot Based on Human Arm Kinematics Model. IEEE Access 2019, 7, 135656 -135664.

AMA Style

Andi Lin, Yucun Tang, Minfeng Gan, Lixin Huang, Shaolong Kuang, Lining Sun. A Virtual Fixtures Control Method of Surgical Robot Based on Human Arm Kinematics Model. IEEE Access. 2019; 7 (99):135656-135664.

Chicago/Turabian Style

Andi Lin; Yucun Tang; Minfeng Gan; Lixin Huang; Shaolong Kuang; Lining Sun. 2019. "A Virtual Fixtures Control Method of Surgical Robot Based on Human Arm Kinematics Model." IEEE Access 7, no. 99: 135656-135664.

Journal article
Published: 29 August 2019 in IEEE Transactions on Neural Systems and Rehabilitation Engineering
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One of the challenges in motor imagery (MI) classification tasks is finding an easy-handled electroencephalogram (EEG) representation method which can preserve not only temporal features but also spatial ones. To fully utilize the features on various dimensions of EEG, a novel MI classification framework is first introduced in this paper, including a new 3D representation of EEG, a multi-branch 3D convolutional neural network (3D CNN) and the corresponding classification strategy. The 3D representation is generated by transforming EEG signals into a sequence of 2D array which preserves spatial distribution of sampling electrodes. The multibranch 3D CNN and classification strategy are designed accordingly for the 3D representation. Experimental evaluation reveals that the proposed framework reaches state-of-the-art classification kappa value level and significantly outperforms other algorithms by 50% decrease in standard deviation of different subjects, which shows good performance and excellent robustness on different subjects. The framework also shows great performance with only nine sampling electrodes, which can significantly enhance its practicality. Moreover, the multi-branch structure exhibits its low latency and a strong ability in mitigating overfitting issues which often occur in MI classification because of the small training dataset.

ACS Style

Xinqiao Zhao; Hongmiao Zhang; Guilin Zhu; Fengxiang You; Shaolong Kuang; Lining Sun. A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2019, 27, 2164 -2177.

AMA Style

Xinqiao Zhao, Hongmiao Zhang, Guilin Zhu, Fengxiang You, Shaolong Kuang, Lining Sun. A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2019; 27 (10):2164-2177.

Chicago/Turabian Style

Xinqiao Zhao; Hongmiao Zhang; Guilin Zhu; Fengxiang You; Shaolong Kuang; Lining Sun. 2019. "A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification." IEEE Transactions on Neural Systems and Rehabilitation Engineering 27, no. 10: 2164-2177.

Conference paper
Published: 06 August 2019 in Algorithms and Data Structures
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Application of 3D printing in the individualized fabrication of biological organ receives more and more attentions. The adopted movement trajectories of nozzle in 3D printing are all based on depositing materials vertically layer by layer. We noticed that the biological organ has always anisotropic property and its natural growing procedure implies a so-called stereotactic fabrication method which can be implemented utilizing robotic techniques. In this research, we proposed and simulated a robot-assisted stereotactic printing method. Kinematics analysis of the robotic manipulator was analyzed. Trajectory planning method for stereotactic operation was designed. Motion simulation analysis of the planned trajectory utilizing manipulator was conducted which validated effectiveness of the proposed printing system from aspects of motion accuracy, flexibility, and potential collisions. The results indicated flexibility of the proposed robot-assisted stereotactic printing technology.

ACS Style

Wanru Fei; Baosen Tan; Shaolong Kuang; Yubo Fan; Wenyong Liu. Simulation Analysis of Trajectory Planning for Robot-Assisted Stereotactically Biological Printing. Algorithms and Data Structures 2019, 154 -162.

AMA Style

Wanru Fei, Baosen Tan, Shaolong Kuang, Yubo Fan, Wenyong Liu. Simulation Analysis of Trajectory Planning for Robot-Assisted Stereotactically Biological Printing. Algorithms and Data Structures. 2019; ():154-162.

Chicago/Turabian Style

Wanru Fei; Baosen Tan; Shaolong Kuang; Yubo Fan; Wenyong Liu. 2019. "Simulation Analysis of Trajectory Planning for Robot-Assisted Stereotactically Biological Printing." Algorithms and Data Structures , no. : 154-162.

Full paper
Published: 22 January 2019 in Advanced Materials Technologies
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Gallium‐based room temperature liquid metal alloys have recently been explored to be an emerging functional material. They have attracted particular attentions in a variety of applications due to their unique properties. Many of the applications are based on the precise control over the motion of liquid metal, and yet, the fact that currently lacking the advanced and reliable controlling methods greatly hinders the potential of liquid metal to be applied in a wider range of fields. In this study, an innovative approach is developed to obtain functional liquid metal (FLM) by modifying it with copper–iron magnetic nanoparticles (Cu–Fe NPs). The magnetic modification process enables the Cu–Fe NPs to be suspended within the liquid metal and form the FLM. The FLM exhibits similar appearance, actuating behaviors, and deformability in alkaline solutions to those of pure liquid metal alloys. Meanwhile, the magnetic modification enables the precise and rapid manipulation of the liquid metal using a magnetic field. Most importantly, for the first time, the precise control and climbing locomotion of the FLM is demonstrated with the interworking of both electric and magnetic fields simultaneously. The remarkable features of the FLM may represent vast potentials toward the development of future intelligent soft robots.

ACS Style

Fangxia Li; Shaolong Kuang; Xiangpeng Li; Jian Shu; Weihua Li; Shi-Yang Tang; Shiwu Zhang. Magnetically- and Electrically-Controllable Functional Liquid Metal Droplets. Advanced Materials Technologies 2019, 4, 1 .

AMA Style

Fangxia Li, Shaolong Kuang, Xiangpeng Li, Jian Shu, Weihua Li, Shi-Yang Tang, Shiwu Zhang. Magnetically- and Electrically-Controllable Functional Liquid Metal Droplets. Advanced Materials Technologies. 2019; 4 (3):1.

Chicago/Turabian Style

Fangxia Li; Shaolong Kuang; Xiangpeng Li; Jian Shu; Weihua Li; Shi-Yang Tang; Shiwu Zhang. 2019. "Magnetically- and Electrically-Controllable Functional Liquid Metal Droplets." Advanced Materials Technologies 4, no. 3: 1.

Conference paper
Published: 01 December 2018 in 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)
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As an emerging multifunctional material, Gallium based room temperature liquid metal attract particular attentions in a variety of applications due to its mobility and deformability. However, accurately control the motion of a liquid metal droplet still remains unrevealed, which restrict the applications of liquid metal in many fields, especially in micro fluidic applications. In this paper, we propose a hybrid control framework to accurately control the motion of a liquid metal droplet in one-dimensional channel filled with aqueous solution. The electrical field is provided by a simple programmable DC power supply. The dynamic model of a liquid metal droplet immersed in fluidic channels is firstly discussed when the electrical field is applied. Then, a region reaching controller is designed to calculate the desired current input to drive the liquid metal droplet to the destination with vision feedback. The effectiveness of the proposed approach is verified by experiments of accurately control a liquid metal Galinstan droplet to destination inside a PMMA fluidics channels. The proposed control approach may generate profound impacts on developing tiny soft robots or micro-fluidic systems that accurately driven by liquid metal droplets.

ACS Style

Jie Xie; Fangxia Li; Jian Shu; Shaolong Kuang; Xiangpeng Li; Shiwu Zhang. Accurately Motion Control of a Liquid Metal Droplet in One-Dimensional Fluidic Channel. 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO) 2018, 934 -939.

AMA Style

Jie Xie, Fangxia Li, Jian Shu, Shaolong Kuang, Xiangpeng Li, Shiwu Zhang. Accurately Motion Control of a Liquid Metal Droplet in One-Dimensional Fluidic Channel. 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO). 2018; ():934-939.

Chicago/Turabian Style

Jie Xie; Fangxia Li; Jian Shu; Shaolong Kuang; Xiangpeng Li; Shiwu Zhang. 2018. "Accurately Motion Control of a Liquid Metal Droplet in One-Dimensional Fluidic Channel." 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO) , no. : 934-939.

Chapter
Published: 11 October 2018 in Advances in Experimental Medicine and Biology
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Cooperation between surgeon and robot is one of the key technologies that limit the robot to be widely used in orthopedic clinics. In this study, the evolution of human-robot cooperation methods and the control strategies for typical human-robot cooperation in robot-assisted orthopedics surgery were reviewed at first. Then an intelligent admittance control method, which combines the fuzzy model reference learning control with the virtual constraint control, is proposed to solve the requirements of intuitive human-robot interaction during orthopedics surgery. That is, a variable damping parameter model of the admittance control based on fuzzy model learning control algorithm is introduced to make the robot move freely by using the reference model of surgeon’s motion equation with the minimum jerk trajectory. And the virtual constraint control method based on the principle of virtual fixture is adopted to make the robot move within the pre-defined area so as to perform more safe surgery. The basic principle and its realization of this intelligent control method are described in details. At last, a test platform is built based on our designed 6 DOF articulated robot. Experiments of safety and precision on acrylic model with this method show that the robot has the ability of better intuitive interaction and the high precision. And the pilot experiment of bone tumor resection on sawbone model shows the effectiveness of this method.

ACS Style

Shaolong Kuang; Yucun Tang; Andi Lin; Shumei Yu; Lining Sun. Intelligent Control for Human-Robot Cooperation in Orthopedics Surgery. Advances in Experimental Medicine and Biology 2018, 1093, 245 -262.

AMA Style

Shaolong Kuang, Yucun Tang, Andi Lin, Shumei Yu, Lining Sun. Intelligent Control for Human-Robot Cooperation in Orthopedics Surgery. Advances in Experimental Medicine and Biology. 2018; 1093 ():245-262.

Chicago/Turabian Style

Shaolong Kuang; Yucun Tang; Andi Lin; Shumei Yu; Lining Sun. 2018. "Intelligent Control for Human-Robot Cooperation in Orthopedics Surgery." Advances in Experimental Medicine and Biology 1093, no. : 245-262.

Conference paper
Published: 01 August 2018 in 2018 IEEE International Conference on Information and Automation (ICIA)
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The stereoscopic radiotherapy robot has more and more advantages in the field of radiotherapy because of its high precision and stability. And the respiration tracking technology of tumor motion plays a key role in the precision radiotherapy of stereoscopic radiotherapy robot. Due to the high complexity and individual differences in modeling for tumor motion during respiration, in order to achieve better accuracy and robustness, this paper proposes a method for establishing a correlation model between tumor and thoracic-abdominal surface model based on 3D point cloud, which more fully reflects three-dimensional surface information and tumor motion correlation. For the proposed method, we present a preliminary study in this paper, including a) body surface modeling scheme; b) the method of establishing a correlation model between tumor and thoracic-abdominal surface model; c) experiments to compare the effect of the two modeling methods, namely the point cloud data modeling and external marker modeling to verify the feasibility of using point cloud data modeling to replace the method of external marker modeling. As a preliminary study, the result of experimental verification lays the foundation for the further correlation model building.

ACS Style

Pengcheng Hou; Rongchuan Sun; Shumei Yu; Shaolong Kuang; Lining Sun. Correlation between Thoracic-abdominal Surface and Tumor Motion based on 3D Point Cloud: A Preliminary Study*. 2018 IEEE International Conference on Information and Automation (ICIA) 2018, 796 -081.

AMA Style

Pengcheng Hou, Rongchuan Sun, Shumei Yu, Shaolong Kuang, Lining Sun. Correlation between Thoracic-abdominal Surface and Tumor Motion based on 3D Point Cloud: A Preliminary Study*. 2018 IEEE International Conference on Information and Automation (ICIA). 2018; ():796-081.

Chicago/Turabian Style

Pengcheng Hou; Rongchuan Sun; Shumei Yu; Shaolong Kuang; Lining Sun. 2018. "Correlation between Thoracic-abdominal Surface and Tumor Motion based on 3D Point Cloud: A Preliminary Study*." 2018 IEEE International Conference on Information and Automation (ICIA) , no. : 796-081.

Conference paper
Published: 01 August 2018 in 2018 IEEE International Conference on Real-time Computing and Robotics (RCAR)
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Magnetic liquid metal soft robot., coated ferromagnetic partials., have extensive potential in aqueous environments due to remark features of easily controlled by more methods. However., previous materials lose movement characteristic so that they are limited in many intriguing applications requiring quickly moving such as motors., robots and so on. Here., we report an innovative soft robot., with magnetism and movement characteristic., manipulated by magnetic field and electric field. Compared with previous researches., the novel liquid metal soft robot is demonstrated to be able to have close velocity with pure liquid metal., when activated by electric field. The preferable virtues of the liquid metal soft robot that it not only displays magnetism but also hold advantageous movement charactistic., performs a significant role in developing diverse unexpected potential applications in the future.

ACS Style

Fangxia Li; Shaolong Kuang; Hao Yang; Shiwu Zhang; Xiangpeng Li. Design and Control of a Liquid Metal Soft Robot by Integration of Electrical and Magnetic Fields. 2018 IEEE International Conference on Real-time Computing and Robotics (RCAR) 2018, 185 -189.

AMA Style

Fangxia Li, Shaolong Kuang, Hao Yang, Shiwu Zhang, Xiangpeng Li. Design and Control of a Liquid Metal Soft Robot by Integration of Electrical and Magnetic Fields. 2018 IEEE International Conference on Real-time Computing and Robotics (RCAR). 2018; ():185-189.

Chicago/Turabian Style

Fangxia Li; Shaolong Kuang; Hao Yang; Shiwu Zhang; Xiangpeng Li. 2018. "Design and Control of a Liquid Metal Soft Robot by Integration of Electrical and Magnetic Fields." 2018 IEEE International Conference on Real-time Computing and Robotics (RCAR) , no. : 185-189.

Conference paper
Published: 01 July 2018 in 2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER)
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In this paper, we aim to achieve the construction of 4-class fNIRS-BCI system. The system performed in assistive-device could help patients with dyskinesia carry out multiple action paradigms of rehabilitation training, and it could provide power assistance to groups of people who carry heavy weights. This paper studied multi-class classification of upper limb movements based on using cerebral hemoglobin information. Seventeen healthy subjects participated in the experiment and accomplished a set of upper limbs action paradigm, including lifting-up, putting down, pulling back and pushing forward. Cerebral hemoglobin information was measured simultaneously by using fNIRS technology. To identify motion intention timely, the data obtained before actual motion was analyzed. Signals were decomposed into three frequency bands by wavelet packet. ReliefF and genetic algorithms were used to select optimal features. A library for support vector machines (LIBSVM) method was applied for pattern recognition and the average recognition rate was 70.6%. The results demonstrated the feasibility of classifying 4-classes of motion intentions based on cerebral hemoglobin information. It has a potential to provide multi-class commands for motion-assistant device.

ACS Style

Liujin He; Chunguang Li; Hedian Jin; Jiacheng Xu; Shaolong Kuang. Motion Intention Classification of Multi-Class Upper Limbs Actions for Brain Machine Interface Applications. 2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER) 2018, 694 -700.

AMA Style

Liujin He, Chunguang Li, Hedian Jin, Jiacheng Xu, Shaolong Kuang. Motion Intention Classification of Multi-Class Upper Limbs Actions for Brain Machine Interface Applications. 2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER). 2018; ():694-700.

Chicago/Turabian Style

Liujin He; Chunguang Li; Hedian Jin; Jiacheng Xu; Shaolong Kuang. 2018. "Motion Intention Classification of Multi-Class Upper Limbs Actions for Brain Machine Interface Applications." 2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER) , no. : 694-700.

Conference paper
Published: 01 June 2018 in 2018 IEEE 14th International Conference on Control and Automation (ICCA)
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Continuum robot is a class of robots renowned for its significant flexibility and manipulability. In recent years, tendon-driven robot, one type of continuum robots, is with compressible and extensible length and bigger working space compared with the non-extensible robot and can travel along the nonlinear spatial curved path. However, existing retractable robots mainly consist of a concentric-like tube, by which it is hard to construct a robot with arbitrary segments, due to the iterative reduction of diameters of multiple tubes and the constraint that diameters of tubes should not be over small to guarantee a necessary stiffness. In this paper, we present a novel tendon-driven continuum robot with extensible length to overcome this shortcoming. The key distinction is that the new design achieves extension based on wire-driven method rather than direct push-pull approach adopted in existing concentric robots. Therefore, continuum robot based on this new design shows higher flexibility and can be with arbitrary segments. Kinematic model of the robot are derived and its workspace is obtained for one and two bending modules. Prototype built demonstrates via experiments the contractible and extensible performance, and the maximal bending angle is measured through experiments. This type of continuum robot may be implemented in therapies for some clinical diseases, like neurosurgery and natural orifice transluminal endoscopic surgery (NOTES).

ACS Style

Yaru Zhang; Huali Sun; Yue Jia; Dan Huang; Ruyu Li; Zhuolin Mao; Yida Hu; Jianbo Chen; Shaolong Kuang; Jie Tang; Xinru Xiao; Baiquan Su. A Continuum Robot with Contractible and Extensible Length for Neurosurgery†. 2018 IEEE 14th International Conference on Control and Automation (ICCA) 2018, 1150 -1155.

AMA Style

Yaru Zhang, Huali Sun, Yue Jia, Dan Huang, Ruyu Li, Zhuolin Mao, Yida Hu, Jianbo Chen, Shaolong Kuang, Jie Tang, Xinru Xiao, Baiquan Su. A Continuum Robot with Contractible and Extensible Length for Neurosurgery†. 2018 IEEE 14th International Conference on Control and Automation (ICCA). 2018; ():1150-1155.

Chicago/Turabian Style

Yaru Zhang; Huali Sun; Yue Jia; Dan Huang; Ruyu Li; Zhuolin Mao; Yida Hu; Jianbo Chen; Shaolong Kuang; Jie Tang; Xinru Xiao; Baiquan Su. 2018. "A Continuum Robot with Contractible and Extensible Length for Neurosurgery†." 2018 IEEE 14th International Conference on Control and Automation (ICCA) , no. : 1150-1155.

Conference paper
Published: 01 June 2018 in 2018 IEEE 14th International Conference on Control and Automation (ICCA)
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Grasping by robotic devices for manipulation and transposition is one of the fundamental and ubiquitous tasks in various domains, including industrial, food and medical fields. Grasping safety is crucial for manipulated object, especially for brittle item or biological target. Thus, contact force, which is a vital factor for grasping safety, has been studied for decades. From the angle of view of system structure design, various kinds of soft gloves are proposed for reducing grasping contact force. However, existing soft gloves are designed to drive fingers from the back of the hand, without considering contact force between finger and manipulated object. The forces between five fingers and object are not equal and often big differences exist between forces on fingers. Aforementioned emerging soft graspers with multiple fingers lack study on balancing contact force of all fingers. Thus, in this paper, a soft hand pad is designed to balance contact force between all fingers. A balancing force control algorithm is developed, which can fulfill balancing force control through adjusting air-pressure of fingers during its grasping object. Experiments verify the proposed soft hand pad design, and the balancing force control algorithm.

ACS Style

Yihua Wang; Hongmin Wang; Mingyang Liu; Peiming Lin; Yida Hu; Ruixue Zhang; Hao Yan; Peixuan Shi; Jie Tang; Ye Zong; Wenyong Liu; Shaolong Kuang; Baiquan Su. A Soft Robotic Hand Pad with Active Balancing Contact Force of All Fingers. 2018 IEEE 14th International Conference on Control and Automation (ICCA) 2018, 1156 -1161.

AMA Style

Yihua Wang, Hongmin Wang, Mingyang Liu, Peiming Lin, Yida Hu, Ruixue Zhang, Hao Yan, Peixuan Shi, Jie Tang, Ye Zong, Wenyong Liu, Shaolong Kuang, Baiquan Su. A Soft Robotic Hand Pad with Active Balancing Contact Force of All Fingers. 2018 IEEE 14th International Conference on Control and Automation (ICCA). 2018; ():1156-1161.

Chicago/Turabian Style

Yihua Wang; Hongmin Wang; Mingyang Liu; Peiming Lin; Yida Hu; Ruixue Zhang; Hao Yan; Peixuan Shi; Jie Tang; Ye Zong; Wenyong Liu; Shaolong Kuang; Baiquan Su. 2018. "A Soft Robotic Hand Pad with Active Balancing Contact Force of All Fingers." 2018 IEEE 14th International Conference on Control and Automation (ICCA) , no. : 1156-1161.

Conference paper
Published: 01 June 2018 in 2018 IEEE 14th International Conference on Control and Automation (ICCA)
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Soft tissue cutting is a fundamental operation in clinical treatments. Autonomous soft tissue cutting using scalpel, one of soft tissue cutting methods, is an emerging field. However, soft tissue displacement during cutting by robotic system is a bottleneck. In this paper, a robotic system is proposed with sucker that can fix soft tissue before and during cutting. The system consists of scalpel fixation and three degrees of freedom (DoF) motion structure and surrounding suckers at the bottom. Cutting curve is abstracted from the cut soft tissue imaged by X-ray. Then the curve is fitted using 10-order B-spline function. The experimental results provide a pilot study towards high precision soft tissue cutting robot.

ACS Style

Peixuan Shi; Bin Cheng; Ye Zong; Yi Gong; Hao Yan; Yida Hu; Huaqing Zhang; Shaolong Kuang; Wenyong Liu; Lixin Wang; Baiquan Su. A Soft Tissue Scalpel Cutting Robotic System with Sucker Fixation†. 2018 IEEE 14th International Conference on Control and Automation (ICCA) 2018, 1162 -1167.

AMA Style

Peixuan Shi, Bin Cheng, Ye Zong, Yi Gong, Hao Yan, Yida Hu, Huaqing Zhang, Shaolong Kuang, Wenyong Liu, Lixin Wang, Baiquan Su. A Soft Tissue Scalpel Cutting Robotic System with Sucker Fixation†. 2018 IEEE 14th International Conference on Control and Automation (ICCA). 2018; ():1162-1167.

Chicago/Turabian Style

Peixuan Shi; Bin Cheng; Ye Zong; Yi Gong; Hao Yan; Yida Hu; Huaqing Zhang; Shaolong Kuang; Wenyong Liu; Lixin Wang; Baiquan Su. 2018. "A Soft Tissue Scalpel Cutting Robotic System with Sucker Fixation†." 2018 IEEE 14th International Conference on Control and Automation (ICCA) , no. : 1162-1167.

Journal article
Published: 11 May 2018 in Applied Sciences
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The traditional postoperative rehabilitation training mode of lower limbs is mostly confined to hospitals or nursing sites. With the increase of postoperative patients, the current shortage of medical resources is obviously not satisfactory, and the medical costs are high, thus it is difficult to apply widely. A new mobile phone application (app) based on plantar pressure analysis is developed to fulfill the requirements of remote postoperative rehabilitation. It is designed, implemented, tested, and used for pilot experiment in conjunction with the system design methodology of the waterfall model. Preliminary testing and a pilot experiment showed that the app has realized basic functions and can achieve patient rehabilitation out of hospitals. The development of the app can shorten the hospitalization time of patients, reduce medical costs, and make up for the current shortage of medical resources. In the future, more experiments will be done to verify the effectiveness of the app.

ACS Style

Xiao Cheng; Xin Mei; Yue Hu; Yinfang Fang; Shuai Wu; Fengxiang You; Shaolong Kuang. Development of an E-Health App for Lower Limb Postoperative Rehabilitation Based on Plantar Pressure Analysis. Applied Sciences 2018, 8, 766 .

AMA Style

Xiao Cheng, Xin Mei, Yue Hu, Yinfang Fang, Shuai Wu, Fengxiang You, Shaolong Kuang. Development of an E-Health App for Lower Limb Postoperative Rehabilitation Based on Plantar Pressure Analysis. Applied Sciences. 2018; 8 (5):766.

Chicago/Turabian Style

Xiao Cheng; Xin Mei; Yue Hu; Yinfang Fang; Shuai Wu; Fengxiang You; Shaolong Kuang. 2018. "Development of an E-Health App for Lower Limb Postoperative Rehabilitation Based on Plantar Pressure Analysis." Applied Sciences 8, no. 5: 766.