Publications by authors named "Shaolong Kuang"

7 Publications

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Stereotactic technology for 3D bioprinting: from the perspective of robot mechanism.

Biofabrication 2021 Aug 13;13(4). Epub 2021 Aug 13.

Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry, Beijing Advanced Innovation Centre for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, People's Republic of China.

Three-dimensional (3D) bioprinting has been widely applied in the field of biomedical engineering because of its rapidly individualized fabrication and precisely geometric designability. The emerging demand for bioprinted tissues/organs with bio-inspired anisotropic property is stimulating new bioprinting strategies. Stereotactic bioprinting is regarded as a preferable strategy for this purpose, which can perform bioprinting at the target position from any desired orientation in 3D space. In this work, based on the motion characteristics analysis of the stacked bioprinting technologies, mechanism configurations and path planning methods for robotic stereotactic bioprinting were investigated and a prototype system based on the double parallelogram mechanism was introduced in detail. Moreover, the influence of the time dimension on stereotactic bioprinting was discussed. Finally, technical challenges and future trends of stereotactic bioprinting within the field of biomedical engineering were summarized.
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http://dx.doi.org/10.1088/1758-5090/ac1846DOI Listing
August 2021

Correlated Skin Surface and Tumor Motion Modeling for Treatment Planning in Robotic Radiosurgery.

Front Neurorobot 2020 12;14:582385. Epub 2020 Nov 12.

School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China.

In robotic radiosurgery, motion tracking is crucial for accurate treatment planning of tumor inside the thoracic or abdominal cavity. Currently, motion characterization for respiration tracking mainly focuses on markers that are placed on the surface of human chest. Nevertheless, limited markers are not capable of expressing the comprehensive motion feature of the human chest and abdomen. In this paper, we proposed a method of respiratory motion characterization based on the voxel modeling of the thoracoabdominal torso. Point cloud data from depth cameras were used to achieve three-dimensional modeling of the chest and abdomen surface during respiration, and a dimensionality reduction algorithm was proposed to extract respiratory features from the established voxel model. Finally, experimental results including the accuracy of voxel model and correlation coefficient were compared to validate the feasibility of the proposed method, which provides enhanced accuracy of target motion correlation than traditional methods that utilized external markers.
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http://dx.doi.org/10.3389/fnbot.2020.582385DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688455PMC
November 2020

A topology optimization method of robot lightweight design based on the finite element model of assembly and its applications.

Sci Prog 2020 Jul-Sep;103(3):36850420936482

School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China.

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.
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http://dx.doi.org/10.1177/0036850420936482DOI Listing
July 2020

Detecting self-paced walking intention based on fNIRS technology for the development of BCI.

Med Biol Eng Comput 2020 May 21;58(5):933-941. Epub 2020 Feb 21.

Key Laboratory of Robotics and System of Jiangsu Province School of Mechanical and Electric Engineering, Soochow University, Suzhou, China.

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.
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http://dx.doi.org/10.1007/s11517-020-02140-wDOI Listing
May 2020

A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification.

IEEE Trans Neural Syst Rehabil Eng 2019 10 29;27(10):2164-2177. Epub 2019 Aug 29.

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 multi-branch 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.
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http://dx.doi.org/10.1109/TNSRE.2019.2938295DOI Listing
October 2019

Intelligent Control for Human-Robot Cooperation in Orthopedics Surgery.

Adv Exp Med Biol 2018;1093:245-262

Robotics and Micro-Systems Center, Soochow University, Suzhou City, Jiangsu Province, People's Republic of China.

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.
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http://dx.doi.org/10.1007/978-981-13-1396-7_19DOI Listing
July 2019

A novel passive/active hybrid robot for orthopaedic trauma surgery.

Int J Med Robot 2012 Dec 13;8(4):458-67. Epub 2012 Jul 13.

Robotics Institute, Beihang University, Beijing, P.R. China.

Background: Image guided navigation systems (IGNS) have been implemented successfully in orthopaedic trauma surgery procedures because of their ability to help surgeons position and orient hand-held drills at optimal entry points. However, current IGNS cannot prevent drilling tools or instruments from slipping or deviating from the planned trajectory during the drilling process. A method is therefore needed to overcome such problems.

Methods: A novel passive/active hybrid robot (the HybriDot) for positioning and supporting surgical tools and instruments while drilling and/or cutting in orthopaedic trauma surgery is presented in this paper. This new robot, consisting of a circular prismatic joint and five passive/active back-drivable joints, is designed to fulfill clinical needs. In this paper, a system configuration and three operational modes are introduced and analyzed. Workspace and layout in the operating theatre (OT) are also analyzed in order to validate the structure design. Finally, experiments to evaluate the feasibility of the robot system are described.

Results: Analysis, simulation, and experimental results show that the novel structure of the robot can provide an appropriate workspace without risk of collision within OT environments during operation. The back-drivable joint mechanism can provide surgeons with more safety and flexibility in operational modes. The mean square value of the positional accuracy of this robot is 0.811 mm, with a standard deviation (SD) of 0.361 mm; the orientation is accurate to within 2.186º, with a SD of 0.932º. Trials on actual patients undergoing surgery for distal locking of intramedullary nails were successfully conducted in one pass using the robot.

Conclusion: This robot has the advantages of having an appropriate workspace, being well designed for human-robot cooperation, and having high accuracy, sufficient rigidity, and easy deployability within the OT for use in common orthopaedic trauma surgery tasks such as screw fixation and drilling assistance.
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http://dx.doi.org/10.1002/rcs.1449DOI Listing
December 2012
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