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Real Time Surgical Instrument Object Detection Using YOLOv7 1

6th EAI International Conference on Robotics and Networks, EAI ROSENET 2022

作者： Zheng, Laiwang Liu, Zhenzhong Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

ISBN: (数字)9783031338267

ISBN: (纸本)9783031338250

With the rapid development of minimally invasive surgery (MIS) in the medical field, surgical robot technology has developed rapidly. Human-machine combined assisted surgical technology has begun to bring good news to the majority of doctors and patients who need surgery. It has gradually become a common medical treatment. Minimally invasive surgery can overcome the shortcomings of traditional surgery. MIS has the advantages of less trauma, less impact on patients, faster recovery, less intraoperative blood loss, and so on. For surgical robots, surgical instruments are important execution components that have been widely concerned and studied in recent years. One of the core technologies of surgical robots is the detection of surgical equipment based on deep learning, which can effectively assist doctors to complete the surgery. Current surgical instrument detection methods need to be improved in real-time performance and accuracy. Therefore, this paper proposes a new real-time detection algorithm, which is based on the deep learning object detection system YOLOv7. The real dataset, which contained information on seven surgical instruments, was selected for training and validation. Experiments show that the method has good precision, recall rate, and mAP, which can be used to improve the ability of robot-assisted doctors to identify instruments during surgery. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object recognition

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design and Research on Flapping Mechanism of Biomimetic Albatross 2

Design and Research on Flapping Mechanism of Biomimetic Alba...

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2022 2nd International Conference on advanced Materials and Mechatronics, ICAMM 2022

作者： Zhang, Haiming Liu, Zhenzhong Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China

In order to solve the problems of low flying efficiency, poor aerodynamic performance of wing and short flying time distance existing in the research of flapping wing aircraft, a kind of albatron-like flapping wing structure with higher flying efficiency is proposed in this paper. The functions of bird wing flutter, folding and gliding are realized by two degrees of freedom control respectively. First, the flying characteristics of albatross are analyzed and the flying characteristics suitable for albatross are summarized. Propose design requirements for bionic design objectives;The bionic structure design is carried out by referring to the physical structure of wing and the flight motion law, and the key parameters such as the size and angle of connecting rod mechanism are analyzed, calculated and optimized. A clamping mechanism is designed to achieve gear stuck in order to achieve gliding kinetic energy. The three-dimensional model of the flapping wing mechanism is built by solid works, and the motion analysis is carried out by using Motion plug-in. The analysis results of key-point parameters are output, which verifies the movement law and requirements of the mechanism to achieve the design objectives. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Wings

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Electrochemical protein biosensors for disease marker detection:progress and opportunities

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Microsystems & Nanoengineering 2024年第3期10卷 1-20页

作者： Lanpeng Guo Yunong Zhao Qing Huang Jing Huang Yanbing Tao Jianjun Chen Hua-Yao Li Huan Liu School of Integrated Circuits Wuhan National Laboratory for OptoelectronicsOptics Valley LaboratoryHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Integrated CircuitsAnhui UniversityHefei 230601China School of Optoelectronic Materials and Technology Jianghan UniversityWuhan 430056China Department of Otorhinolaryngology Union HospitalTongji Medical CollegeHuazhong University of Science and Technology1277 Jiefang AvenueWuhan 430022China Wenzhou Institute of Advanced Manufacturing Technology Huazhong University of Science and TechnologyWenzhou 325000China

The development of artificial intelligence-enabled medical health care has created both opportunities and challenges for next-generation biosensor *** are extensively used as biological macromolecular markers in disease diagnosis and the analysis of therapeutic *** protein biosensors have achieved desirable specificity by using the specific antibody–antigen binding principle in ***,the active centers of protein biomarkers are surrounded by a peptide matrix,which hinders charge transfer and results in insufficient sensor ***,electrode-modified materials and transducer devices have been designed to increase the sensitivity and improve the practical application prospects of electrochemical protein *** this review,we summarize recent reports of electrochemical biosensors for protein biomarker *** highlight the latest research on electrochemical protein biosensors for the detection of cancer,viral infectious diseases,inflammation,and other *** corresponding sensitive materials,transducer structures,and detection principles associated with such biosensors are also addressed ***,we present an outlook on the use of electrochemical protein biosensors for disease marker detection for the next few years.

关键词： diagnosis specificity Electrochemical

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Structure design and dynamic modelling of a novel modular self-reconfigurable robot

Structure design and dynamic modelling of a novel modular se...

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IEEE International Conference on Mechatronics and Automation

作者： Jie Huang Weimin Ge Xiaofeng Wang Jun Liu Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System Tianjin University of Technology Tianjin China

ISBN: (纸本)9781509023974

Reconfigurability of the modular robot is becoming curial to be a high flexibility for the wide varieties of tasks and environments. In this paper, a novel self-reconfigurable modular robot called M 2 sbot is designed, which has the approximate cuboid shaping structure. The unit model is with one active and five passive connection surfaces, compact structure and flexible motion. It is characterized by using the unique hook-claw docking mechanism as the docking part of the neighbor modular. And the responding control system based on STM32F103VET6 is also implemented. The forward kinematic equations of the chain robot are established, and then the dynamic equation is generated by the recursive Newton-Euler method based on the global matrix description. Finally, the calculation and simulation analysis of the six-module configuration with two branches demonstrates the feasibility of the proposed method in the generation of motion equation.

关键词： Gears Mathematical model Kinematics DC motors Robot sensing systems Robot kinematics

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Interactive Cloud Detection Based on Dynamic Mode Decomposition

Interactive Cloud Detection Based on Dynamic Mode Decomposit...

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2024 International Conference on Information Technology, Data Science, and Optimization, I-DO 2024

作者： Li, Yilong Yang, Lu Qiu, Xiaobin Bi, Chongke Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China Tianjin Key Laboratory for Oceanic Meteorology and Tianjin Institute of Meteorological Science Tianjin China Tianjin University Tianjin China

ISBN: (纸本)9798400709180

Cloud detection can address data quality and analytical accuracy issues caused by cloud cover in satellite imagery, significantly enhancing image usability. Existing cloud detection methods still have the problem of detecting a certain amount of ground and sea surface as clouds, as well as some cloud regions that are missed, resulting in a decrease in the accuracy of cloud detection. Aiming at the above problems, an interactive cloud detection method based on Dynamic Mode Decomposition is proposed. Based on the fact that clouds are constantly moving, the dynamic mode decomposition can be utilized to detect the characteristics of moving objects, and the dynamic clouds are detected, avoiding the detection of the ground and sea surface as clouds. Although static clouds rarely appear, to ensure the robustness of the algorithm, we design an interactive static cloud detection algorithm for the users, which solve the problem of missed detection and further improves the accuracy of cloud detection. To assess the effectiveness of the algorithm, the four different types of clouds of floccus, undulatus, vortex clouds, and stratocumulus are detected, the experimental outcomes demonstrate the effectiveness and robustness of the algorithm. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Dynamic mode decomposition

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Visual Servoing of Magnetic Swimming Robot Based on Mean Shift and Fast Template Matching Algorithm

Visual Servoing of Magnetic Swimming Robot Based on Mean Shi...

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IEEE International Conference on Robotics and Biomimetics

作者： Hongbiao Xiang Tilei Zhang Mengwei Li Shoujun Wang Xiuping Yang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin China

The actuation and control of mini-scale swimming robots have exhibit promising potential in limited and constrained environments, such as biomedical, micro-assembly and microfluidic applications. However, closed-loop control is still a challenging for the precision and repeatability in those applications. In this paper, a new type of soft-micro swimming robot based on magnetoelastic composite material is designed, and the swimmer can move freely on the water surface controlled by a rotating magnetic field with visual servoing. The visual feedback control strategy is proposed based on Mean Shift Algorithm and Fast Template Matching. The algorithm includes three parts: prediction, template matching, target positioning and template updating. To understand the characteristics of the swimmer, the relationship between swimming speed and magnetic field strength and frequency is verified by the algorithm in experiments. Furthermore, the proposed path following method with visual servoing applied in this control system. The experimental results show that the algorithm runs fast, has high accuracy and good real-time performance, and can provide great potential in mini-scale robot applications.

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An Automatic Method for Brain Tumors Segmentation Based on Deep Convolutional Neural Network

An Automatic Method for Brain Tumors Segmentation Based on D...

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2021 IEEE International Conference on Medical Imaging Physics and Engineering, ICMIPE 2021

作者： Lin, Hui Zhang, Benjian Guo, Xin Guo, Dong Jing, Jia Huiyuan, Luo Yumeng, Zhao Hu, Min Ren, Fuji School of Physics Hefei University of Technology Hefei China School of Computer and Information Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei China School of Computer and Information Hefei University of Technology Hefei China Graduate School of Advanced Technology and Science University of Tokushima Tokushima Japan

ISBN: (纸本)9781665426084

[Purpose] Accurate outline of tumor targets is critical to a high quality radiotherapy plan. Manual segmentation is of great workload and has a strong artificial subjectivity. Using deep learning method to assist automatically segmenting of tumor target is the penetration and application of artificial intelligence in medicine. [Methods] A 6-layer model of deep Convolution Neural Network (CNN) has been constructed by taking advantage of different types of layers for brain tumor segmentation. This model is a 6 layer CNN model (6-CNN) composed of three convolution layers, two pool layers and one full connection layer. To obtain enough samples for 6-CNN model training, a patch-based technology has been adopted. That is to successively extract a local area from the whole image as a patch. And the center pixel value is taken as the pixel value of the whole patch. Similarly, the label of the center pixel is also taken as the label of the whole patch. Thus the 6-CNN model transforms the brain tumor image segmentation into patch classification based on the excellent classification characteristics of deep convolution neural network. The model combines the local features of patch, the information extracted from shallow network and the global features to predict the category label of the central pixel of patch. [Results] The model is validated on BRATS 2015 dataset and results show that the segmentation accuracy can be up to Dice Similarity Coefficient (DSC) 90\%\pm 4\%. [Conclusions] An automatic deep CNN segmentation model for brain tumors has been constructed based on MRI image patches, which is expected to assist or even substitute the manual segmentation of brain tumors. © 2021 IEEE.

关键词： Neural network models

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A QoS-Aware DRL-Based Service Switching Approach for Vehicular Edge computing

A QoS-Aware DRL-Based Service Switching Approach for Vehicul...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Xiaowei Wang Zixian Qiu Yang Li Hongmao Qin Ming Gao State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Wuxi Intelligent Control Research Institute of Hunan University Changsha China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Changsha China

To meet the requirements of low latency and high reliability of vehicular computing, vehicular services need to be offloaded to multi-access edge computing (MEC) servers. However, due to the mobility of connected vehicles and the limited coverage of roadside units (RSUs), vehicular services need to be adaptively switched. In order to ensure the quality of service (QoS) in the process of vehicular service switching, a service switching approach based on deep reinforcement learning is proposed in this paper. Firstly, the optimization problem model is established by considering the QoS, service migration cost, and latency. Secondly, the problem is decomposed into several subproblems and transformed into Markov decision processes (MDPs). Finally, a deep reinforcement learning-based algorithm is employed to find the optimal service migration strategy. Simulation results indicate that the proposed approach can effectively ensure the QoS compared to the baseline approaches.

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design and realization of 3D NOC multicast router base on multicast rotational routing arithmetic

Design and realization of 3D NOC multicast router base on mu...

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International Conference on computing and Networking Technology (ICCNT)

作者： Wei Wang Runfeng Li Fang Fang Tian Chen Fuji Ren Jun Liu Xi Wu Hefei University of Technology Hefei China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine China

ISBN: (纸本)9781479926978

Traditional 3D NoC router may encounter the situations of congestion and hot spot. And it also doesn't have the function of multicast. In this paper, we present a new routing arithmetic called Multicast Rotational Routing Arithmetic (MRRA). It can handle several destination addresses at the same time, recombine packets, sent the same data to the different destination nodes, and avoid the congestion. The proposed algorithm is implemented by the new multicast 3D NoC router which is also proposed in this paper. The 3D NoC router is designed in Verilog HDL, simulated by Modelsim, synthesized and prototyped by Synplify and FPGA respectively. The experiment results show that the multicast router of MRRA can achieve a very good performance in terms of throughput and delay. The increased area utilization also can be tolerated.

关键词： Routing Three-dimensional displays Throughput Algorithm design and analysis Ports (Computers) Hardware design languages Integrated circuits

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Interactive Mixed Reality Cooking Assistant for Unskilled Operating Scenario 12th

Interactive Mixed Reality Cooking Assistant for Unskilled Op...

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12th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020

作者： Zhai, Ke-yu Cao, Yi-ming Hou, Wen-jun Li, Xue-ming School of Digital Media and Design Arts Beijing University of Posts and Telecommunications Beijing100876 China Beijing Key Laboratory of Network and Network Culture Beijing University of Posts and Telecommunications Beijing100876 China Digital Media and Intelligent Computing Laboratory Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9783030496975

As the further development of virtual reality technology, mixed reality (MR) promotes the innovation of human-computer interaction. It can integrate virtual information (objects, pictures, videos, etc.) into the real environment, and directly interact with people. It can greatly improve the efficiency of information reception, reduce the cost of understanding and learning, and improve the fluency and accuracy of operational tasks. In the kitchen scene, when the novices cook according to the recipe, they usually do not perform well in memory and learning, which causes many problems in the cooking process. Therefore, we propose an interactive intelligent cooking system design, which focuses on the five kinds of information that novices need most help in the cooking process, and subverts the traditional recipe with MR presentation. The experiment also shows that the intelligent cooking system can make up for the guidance to novice which is easy to be ignored by traditional recipes, and can effectively improve the user experience of novices. © 2020, Springer Nature Switzerland AG.

关键词： Mixed reality

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