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Review of Key Technologies for Developing Personalized Lower Limb Rehabilitative Exoskeleton Robots TAO Jing, (陶璟), ZHOU Zhenhuan (周振欢) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 16-28.   DOI: 10.1007/s12204-022-2452-3 Abstract （1146）      PDF（pc） （1179KB）（801）       Knowledge map    Save Rehabilitative training and assistance to daily living activities play critical roles in improving the life quality of lower limb dyskinesia patients and older people with motor function degeneration. Lower limb rehabilitative exoskeleton has a promising application prospect in support of the above population. In this paper, critical technologies for developing lower limb rehabilitative exoskeleton for individualized user needs are identi- fied and reviewed, including exoskeleton hardware modularization, bionic compliant driving, individualized gait planning and individual-oriented motion intention recognition. Inspired by the idea of servitization, potentials in exoskeleton product-service system design and its enabling technologies are then discussed. It is suggested that future research will focus on exoskeleton technology and exoskeleton-based service development oriented to an individual’s physical features and personalized requirements to realize better human-exoskeleton coordination in terms of technology, as well as accessible and high-quality rehabilitation and living assistance in terms of utility. Reference | Related Articles | Metrics | Comments（0）

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Review of Power-Assisted Lower Limb Exoskeleton Robot HE Guisong (贺贵松), HUANG Xuegong (黄学功), LI Feng (李峰), WANG Huixing (汪辉兴) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 1-15.   DOI: 10.1007/s12204-022-2489-3 Abstract （1079）      PDF（pc） （1195KB）（234）       Knowledge map    Save Power-assisted lower limb exoskeleton robot is a wearable intelligent robot system involving mechanics,materials, electronics, control, robotics, and many other fields. The system can use external energy to provide additional power to humans, enhance the function of the human body, and help the wearer to bear weight that is previously unbearable. At the same time, employing reasonable structure design and passive energy storage can also assist in specific actions. First, this paper introduces the research status of power-assisted lower limb exoskeleton robots at home and abroad, and analyzes several typical prototypes in detail. Then, the key technologies such as structure design, driving mode, sensing technology, control method, energy management, and human-machine coupling are summarized, and some common design methods of the exoskeleton robot are summarized and compared. Finally, the existing problems and possible solutions in the research of power-assisted lower limb exoskeleton robots are summarized, and the prospect of future development trend has been analyzed. Reference | Related Articles | Metrics | Comments（0）

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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) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 370-381.   DOI: 10.1007/s12204-023-2607-x Abstract （798）      PDF（pc） （1017KB）（220）       Knowledge map    Save 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. Reference | Related Articles | Metrics | Comments（0）

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Multi-Agent Path Planning Method Based on Improved Deep Q-Network in Dynamic Environments LI Shuyi (李舒逸), LI Minzhe (李旻哲), JING Zhongliang∗ (敬忠良) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 601-612.   DOI: 10.1007/s12204-024-2732-1 Abstract （644）      PDF（pc） （1213KB）（263）       Knowledge map    Save The multi-agent path planning problem presents significant challenges in dynamic environments, primarily due to the ever-changing positions of obstacles and the complex interactions between agents’ actions. These factors contribute to a tendency for the solution to converge slowly, and in some cases, diverge altogether. In addressing this issue, this paper introduces a novel approach utilizing a double dueling deep Q-network (D3QN), tailored for dynamic multi-agent environments. A novel reward function based on multi-agent positional constraints is designed, and a training strategy based on incremental learning is performed to achieve collaborative path planning of multiple agents. Moreover, the greedy and Boltzmann probability selection policy is introduced for action selection and avoiding convergence to local extremum. To match radar and image sensors, a convolutional neural network - long short-term memory (CNN-LSTM) architecture is constructed to extract the feature of multi-source measurement as the input of the D3QN. The algorithm’s efficacy and reliability are validated in a simulated environment, utilizing robot operating system and Gazebo. The simulation results show that the proposed algorithm provides a real-time solution for path planning tasks in dynamic scenarios. In terms of the average success rate and accuracy, the proposed method is superior to other deep learning algorithms, and the convergence speed is also improved. Reference | Related Articles | Metrics | Comments（0）

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Multi-Robot Task Allocation Using Multimodal Multi-Objective Evolutionary Algorithm Based on Deep Reinforcement Learning MIAO Zhenhua(苗镇华), HUANG Wentao(黄文焘), ZHANG Yilian(张依恋), FAN Qinqin(范勤勤) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 377-387.   DOI: 10.1007/s12204-023-2679-7 Abstract （623）      PDF（pc） （975KB）（231）       Knowledge map    Save The overall performance of multi-robot collaborative systems is significantly affected by the multirobot task allocation. To improve the effectiveness, robustness, and safety of multi-robot collaborative systems,a multimodal multi-objective evolutionary algorithm based on deep reinforcement learning is proposed in this paper. The improved multimodal multi-objective evolutionary algorithm is used to solve multi-robot task allocation problems. Moreover, a deep reinforcement learning strategy is used in the last generation to provide a high-quality path for each assigned robot via an end-to-end manner. Comparisons with three popular multimodal multi-objective evolutionary algorithms on three different scenarios of multi-robot task allocation problems are carried out to verify the performance of the proposed algorithm. The experimental test results show that the proposed algorithm can generate sufficient equivalent schemes to improve the availability and robustness of multirobot collaborative systems in uncertain environments, and also produce the best scheme to improve the overall task execution efficiency of multi-robot collaborative systems. Reference | Related Articles | Metrics | Comments（0）

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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) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 289-295.   DOI: 10.1007/s12204-023-2602-2 Abstract （510）      PDF（pc） （1156KB）（168）       Knowledge map    Save 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. Reference | Related Articles | Metrics | Comments（0）

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Development of Rehabilitation and Assistive Robots in China: Dilemmas and Solutions ZHAO Lingling1*(赵玲玲),GUO Yao2(郭遥) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 382-390.   DOI: 10.1007/s12204-023-2596-9 Abstract （461）      PDF（pc） （367KB）（78）       Knowledge map    Save 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. Reference | Related Articles | Metrics | Comments（0）

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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) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 312-322.   DOI: 10.1007/s12204-023-2579-x Abstract （459）      PDF（pc） （2606KB）（66）       Knowledge map    Save 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. Reference | Related Articles | Metrics | Comments（0）

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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) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 360-369.   DOI: 10.1007/s12204-023-2603-1 Abstract （438）      PDF（pc） （734KB）（49）       Knowledge map    Save 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. Reference | Related Articles | Metrics | Comments（0）

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Numerical Study on Separation of Circulating Tumor Cell Using Dielectrophoresis in a Four-Electrode Microfluidic Device WANG Yukuna (王雨坤), DING Xiantingb (丁显廷), ZHANG Zhinana (张执南) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 391-.   DOI: 10.1007/s12204-022-2459-9 Abstract （432）      PDF（pc） （1462KB）（311）       Knowledge map    Save This numerical study proposes a cell sorting technique based on dielectrophoresis (DEP) in a microfluidic chip. Under the joint effect of DEP and fluid drag, white blood cells and circulating tumor cells are separated because of different dielectric properties. First, the mathematical models of device geometry, single cell, DEP force, electric field, and flow field are established to simulate the cell motion. Based on the simulation model, important boundary parameters are discussed to optimize the cell sorting ability of the device. A proper matching relationship between voltage and flow rate is then provided. The inlet and outlet conditions are also investigated to control the particle motion in the flow field. The significance of this study is to verify the cell separating ability of the microfluidic chip, and to provide a logistic design for the separation of rare diseased cells. Reference | Related Articles | Metrics | Comments（0）

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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) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 296-306.   DOI: 10.1007/s12204-023-2595-x Abstract （420）      PDF（pc） （2087KB）（95）       Knowledge map    Save 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. Reference | Related Articles | Metrics | Comments（0）

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Boosting Unsupervised Domain Adaptation with Soft Pseudo-Label and Curriculum Learning ZHANG Shengjia(张晟嘉), LIN Tiancheng(林天成), XU Yi(徐奕) J Shanghai Jiaotong Univ Sci    2023, 28 (6): 703-716.   DOI: 10.1007/s12204-022-2487-5 Abstract （420）      PDF（pc） （963KB）（115）       Knowledge map    Save By leveraging data from a fully labeled source domain, unsupervised domain adaptation (UDA) improves classification performance on an unlabeled target domain through explicit discrepancy minimization of data distribution or adversarial learning. As an enhancement, category alignment is involved during adaptation to reinforce target feature discrimination by utilizing model prediction. However, there remain unexplored problems about pseudo-label inaccuracy incurred by wrong category predictions on target domain, and distribution deviation caused by overfitting on source domain. In this paper, we propose a model-agnostic two-stage learning framework, which greatly reduces flawed model predictions using soft pseudo-label strategy and avoids overfitting on source domain with a curriculum learning strategy. Theoretically, it successfully decreases the combined risk in the upper bound of expected error on the target domain. In the first stage, we train a model with distribution alignment-based UDA method to obtain soft semantic label on target domain with rather high confidence. To avoid overfitting on source domain, in the second stage, we propose a curriculum learning strategy to adaptively control the weighting between losses from the two domains so that the focus of the training stage is gradually shifted from source distribution to target distribution with prediction confidence boosted on the target domain. Extensive experiments on two well-known benchmark datasets validate the universal effectiveness of our proposed framework on promoting the performance of the top-ranked UDA algorithms and demonstrate its consistent superior performance. Reference | Related Articles | Metrics | Comments（0）

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Review on Anti-Frost Technology Based on Microchannel Heat Exchanger YE Zhenhong(叶振鸿), WANG Wei(王炜), LI Xinhua(李新华), CHEN Jiangping(陈江平) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 161-178.   DOI: 10.1007/s12204-022-2539-x Abstract （397）      PDF（pc） （4397KB）（106）       Knowledge map    Save Frosting is an inevitable adverse phenomenon in many fields such as industrial refrigeration, cryogenics, and heat pump air conditioning, which may influence the efficiency of the equipment and increase the energy consumption of the system. The complicated louvered-fin structure and fluid-channels arrangements of the microchannel heat exchanger (HEX) will affect the heat transfer performance and frosting characteristics. First, this article analyzes different factors such as refrigerant distribution, refrigerant flow pattern, and HEX surface temperature distribution. Further, combined with the features of the microchannel HEX, the existing anti-frosting technologies and various methods of surface treatment for anti-frosting are summarized. The review focuses on the preparation of superhydrophobic surfaces and their superior properties. Furthermore, the internal mechanism is analyzed in conjunction with the relevant research of our group. Superhydrophobic character has excellent anti-frosting performance and heat transfer performance, which is of great significance for improving energy-saving and system performance. Finally, the future development of superhydrophobic surface technology is analyzed and prospected. Reference | Related Articles | Metrics | Comments（0）

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Video-Based Detection of Epileptic Spasms in IESS: Modeling, Detection, and Evaluation DING Lihui1, 2(丁黎辉), FU Lijun1, 3 (付立军), YANG Guang4(杨光), WAN Lin4, 5 (万林), CHANG Zhijun7(常志军) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 1-9.   DOI: 10.1007/s12204-024-2789-x Abstract （395）      PDF（pc） （712KB）（50）       Knowledge map    Save Behavioral scoring based on clinical observations remains the gold standard for screening, diagnosing,and evaluating infantile epileptic spasm syndrome (IESS). The accurate identification of seizures is crucial for clinical diagnosis and assessment. In this study, we propose an innovative seizure detection method based on video feature recognition of patient spasms. To capture the temporal characteristics of the spasm behavior presented in the videos effectively, we incorporate asymmetric convolution and convolution–batch normalization–ReLU (CBR) modules. Specifically within the 3D-ResNet residual blocks, we split the larger convolutional kernels into two asymmetric 3D convolutional kernels. These kernels are connected in series to enhance the ability of the convolutional layers to extract key local features, both horizontally and vertically. In addition, we introduce a 3D convolutional block attention module to enhance the spatial correlations between video frame channels efficiently. To improve the generalization ability, we design a composite loss function that combines cross-entropy loss with triplet loss to balance the classification and similarity requirements. We train and evaluate our method using the PLA IESS-VIDEO dataset, achieving an average seizure recognition accuracy of 90.59%, precision of 90.94%, and recall of 87.64%. To validate its generalization capability further, we conducted external validation using six different patient monitoring videos compared with assessments by six human experts from various medical centers. The final test results demonstrate that our method achieved a recall of 0.647 6, surpassing the average level achieved by human experts (0.559 5), while attaining a high F1-score of 0.721 9. These findings have substantial significance for the long-term assessment of patients with IESS. Reference | Related Articles | Metrics | Comments（0）

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Calibration Technology of Optical Fiber Strain Sensor CHEN Gang(陈刚), LIU Hongyue(刘宏月), GAO Ruiriang(高瑞翔) J Shanghai Jiaotong Univ Sci    2023, 28 (5): 551-559.   DOI: 10.1007/s12204-022-2406-9 Abstract （359）      PDF（pc） （1122KB）（147）       Knowledge map    Save As one of the hotspots of sensing technology at present, optical fiber sensor has the characteristics of small size, anti-electromagnetic interference, and easy networking, which plays an irreplaceable role in multiphysics parameter monitoring of complex electromagnetic environments. The precise calibration of the optical fiber strain sensor has great practical value in prolonging the survival rate of the sensor, improving the measurement accuracy, and meeting the needs of long-term monitoring. By reviewing the research status of strain sensor calibration method and fiber optic strain sensor calibration method, the advantages and disadvantages of the main methods are analyzed separately from the static and dynamic perspectives, and the development prospect of the calibration technology of optic fiber strain sensor is summarized. Reference | Related Articles | Metrics | Comments（0）

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Applications of Artificial Intelligence in Cardiac Electrophysiology and Clinical Diagnosis with Magnetic Resonance Imaging and Computational Modeling Techniques ZHAN Heqing1 (詹何庆), HAN Guilai1 (韩贵来), WEI Chuan’an1 (魏传安), LI Zhiqun2* (李治群) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 53-65.   DOI: 10.1007/s12204-023-2628-5 Abstract （355）      PDF（pc） （232KB）（23）       Knowledge map    Save The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases, which are the most common cause of morbidity and mortality worldwide, have gotten a lot of attention and been widely explored in recent decades. Along the way, techniques such as medical imaging, computing modeling, and artificial intelligence (AI) have always played significant roles in above studies. In this article, we illustrated the applications of AI in cardiac electrophysiological research and disease prediction. We summarized general principles of AI and then focused on the roles of AI in cardiac basic and clinical studies incorporating magnetic resonance imaging and computing modeling techniques. The main challenges and perspectives were also analyzed. Reference | Related Articles | Metrics | Comments（0）

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Unsupervised Oral Endoscope Image Stitching Algorithm HUANG Rong (黄荣), CHANG Qing∗ (常青), ZHANG Yang （张扬） J Shanghai Jiaotong Univ Sci    2024, 29 (1): 81-90.   DOI: 10.1007/s12204-022-2513-7 Abstract （355）      PDF（pc） （5774KB）（78）       Knowledge map    Save Oral endoscope image stitching algorithm is studied to obtain wide-field oral images through registration and stitching, which is of great significance for auxiliary diagnosis. Compared with natural images, oral images have lower textures and fewer features. However, traditional feature-based image stitching methods rely heavily on feature extraction quality, often showing an unsatisfactory performance when stitching images with few features. Moreover, due to the hand-held shooting, there are large depth and perspective disparities between the captured images, which also pose a challenge to image stitching. To overcome the above problems, we propose an unsupervised oral endoscope image stitching algorithm based on the extraction of overlapping regions and the loss of deep features. In the registration stage, we extract the overlapping region of the input images by sketching polygon intersection for feature points screening and estimate homography from coarse to fine on a three-layer feature pyramid structure. Moreover, we calculate loss using deep features instead of pixel values to emphasize the importance of depth disparities in homography estimation. Finally, we reconstruct the stitched images from feature to pixel, which can eliminate artifacts caused by large parallax. Our method is compared with both feature-based and previous deep-based methods on the UDIS-D dataset and our oral endoscopy image dataset. The experimental results show that our algorithm can achieve higher homography estimation accuracy, and better visual quality, and can be effectively applied to oral endoscope image stitching. Reference | Related Articles | Metrics | Comments（0）

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Medicine-Engineering Interdisciplinary Research Based on Bibliometric Analysis: A Case Study on Medicine-Engineering Institutional Cooperation of Shanghai Jiao Tong University WANG Qingwen (王庆稳)，CUI Tingting (崔婷婷)，DENG Peiwen* (邓珮雯) J Shanghai Jiaotong Univ Sci    2023, 28 (6): 841-856.   DOI: 10.1007/s12204-022-2418-5 Abstract （348）      PDF（pc） （1829KB）（752）       Knowledge map    Save This article aims to provide reference for medicine-engineering interdisciplinary research. Targeted at the scientific literature and patent literature published by Shanghai Jiao Tong University, this article attempts to set up co-occurrence matrix of medicine-engineering institutional information which was extracted from address fields of the papers, so as to construct the medicine-engineering intersection datasets. The dataset of scientific literature was analyzed using bibliometrics and visualization methods from multiple dimensions, and the most active factors, such as trends of output, journal and subject distribution, were identified from the indicators of category normalized citation impact (CNCI), times cited, keywords, citation topics and the degree of medicineengineering interdisplinary. Research on hotspots and trends was discussed in detail. Analyses of the dataset of patent literature showed research themes and measured the degree for technology convergence of medicineengineering. Reference | Related Articles | Metrics | Comments（0）

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Early Detection Methods of Deep Tissue Pressure Injuries: A Systematic Review JIA Jingyil (贾菁怡)，LI Zhengyi1,2 (李正裔)，PENG Linjing1 (彭琳晶)，YAO Yifeil* (姚怡飞) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 526-.   DOI: 10.1007/s12204-022-2518-2 Abstract （343）      PDF（pc） （552KB）（157）       Knowledge map    Save Deep tissue pressure injuries (DTPIs) have witnessed a growing prevalence in hospitals and other health care units especially among individuals with pathological conditions that give rise to restricted mobility, impaired sensation, and reduced tissue tolerance. The etiology of DTPIs has been a subject of controversy, to which several explanatory models have been proposed, including direct mechanical insult, ischemia-reperfusion, lymphatic occlusion, and inflammatory cytokines. In line with these pathophysiological scenarios, ultrasound, subepidermal moisture detection, and biomarker technologies have been proposed as potential early detection methods of DTPIs. This paper provides a systematic review involving these three methods. The conclusion is that combining and implementing these methods at different time periods during DTPIs development and progression respectively is likely to be the most universal, effective and promising way for DTPIs diagnosis. Reference | Related Articles | Metrics | Comments（0）

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Establishment of a Refined Brain Model for Evaluating Implantation Behavior of Neural Electrode and Research of its Simulated Behavior HE Yuxcin (贺雨欣), ZHANG Wenguang (张文光), XU Haotian (胥浩天), XU Yifan (徐倚帆), XU Liyue (许李悦) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 401-.   DOI: 10.1007/s12204-022-2523-5 Abstract （342）      PDF（pc） （1512KB）（134）       Knowledge map    Save The long-term reliability of the neural electrode is closely related to its implantation behavior. In orderto realize the quantitative research of the implantation behavior in a low-cost and accurate way, a refined brainmodel containing meninges is proposed. First, the expected simulation material was selected through measuringthe elastic modulus based on the method of atomic force microscope indentation technique. As a result, the 2%(mass fraction) agarose gel simulated the gray and white matter, the 7 : 1 (volume ratio) polydimethylsiloxane(PDMS) sheet simulated the pia mater, and the polyvinyl chloride (PVC) film simulated the dura mater. Second,based on designing a three-layer structure mold, the brain model was prepared by inverted pouring to realizea flat implantation surface. Finally, the simulation behavior of the brain model was investigated with the ratbrain as a reference. For mechanical behavior of implantation, the implantation force experienced two peaks bothin the brain model and the rat brain, maximum values of which were 10.17 mN and 7.69 mN respectively. Thelarger implantation force in the brain model will increase the strength requirement for the electrode, but reducethe risk of buckling of that in practical application. For humoral dissolution behavior, the dissolution rates ofthe polyethylene glycol (PEG) coating of the electrode in the brain model and rat brain were 7 000 μm3/s and5 600 μm3/s, respectively. The faster dissolution rate in the brain model will cause the larger thickness of thecoating design but provide sufficient implantable time in practical application. The establishment of the brainmodel and the research of its simulated behavior are beneficial to the size design of the electrode substrate andcoating, and research of the implantation mechanism, and further increase the functional life of the electrode. Reference | Related Articles | Metrics | Comments（0）

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Substrate Stiffness and Topography Affect the Morphology of Human Fibroblasts in Mechanical Microenvironment LIU Yang-,2 (刘阳), WANG Yajing- (王雅靖)，WEN Daweil (温大渭)，ZHANG Quanyoul (张全有), WANG Li (王立)，AN Meiwen1* (安美文), LIU Yong3* (刘勇) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 495-.   DOI: 10.1007/s12204-022-2542-2 Abstract （329）      PDF（pc） （1268KB）（44）       Knowledge map    Save Hyperplastic scar is a common fibrotic disease that may ultimately lead to severe dysfunction anddeformity, causing physical and psychological distress. Therefore, we aim to evaluate the effect of the mechanicalmicroenvironment of scar substrates on the morphology of human fibroblasts (HFbs). The micro-modular fabrication technique was used to design a new cross-groove topology and to construct four elastic substrates withthe stiffness of 19.3 kPa and 90.1 kPa coupled with parallel groove and cross groove, respectively, to simulate themechanical microenvironment of skin wounds and scar tissues. The morphological changes in HFbs in differentsubstrates were observed, and the changes in the cell-long axis length, area, and the angle between cell-long axisand grooves were recorded. Immunofluorescence staining was performed to observe the distribution of microfilaments. The results indicated that substrate stiffness and topography affected the morphology of HFbs. The cellswere elongated in parallel grooves as well as in the area where cross grooves restricted groove length, the celllength was restricted, and the angle between the long axis and the groove was increased. The topography exertedno significant effect on the cell area, but the cell area increased with increasing the stiffness. The parallel groovepromoted the expression of the F-actin to a certain extent, and the fluorescence intensity of F-actin decreased withincreasing the stiffness. Studying the effect of the mechanical microenvironment of substrates on HFb morphologyis of great importance for understanding the mechanisms of scar formation and prevention. Reference | Related Articles | Metrics | Comments（0）

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Medical Image Encryption Based on Fisher-Yates Scrambling and Filter Diffusion HUANG Jiaxin (黄佳鑫), GUO Yali (郭亚丽), GAO Ruoyun (高若云),LI Shanshan∗ (李珊珊) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 136-152.   DOI: 10.1007/s12204-023-2618-7 Abstract （326）      PDF（pc） （8076KB）（13）       Knowledge map    Save A medical image encryption is proposed based on the Fisher-Yates scrambling, filter diffusion and S-box substitution. First, chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system, which is used for the scrambling, substitution and diffusion processes. The three-dimensional Fisher-Yates scrambling, S-box substitution and diffusion are employed for the first round of encryption. The chaotic sequence is adopted for secondary encryption to scramble the ciphertext obtained in the first round. Then, three-dimensional filter is applied to diffusion for further useful information hiding. The key to the algorithm is generated by the combination of hash value of plaintext image and the input parameters. It improves resisting ability of plaintext attacks. The security analysis shows that the algorithm is effective and efficient. It can resist common attacks. In addition, the good diffusion effect shows that the scheme can solve the differential attacks encountered in the transmission of medical images and has positive implications for future research. Reference | Related Articles | Metrics | Comments（0）

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Real-Time Calculation Method for Temperature Distribution of Temperature-Controlled Radiofrequency Ablation WANG Xuewei (王雪维)，WANG Yifei (王逸飞)，ZHANG Aili* (张爱丽) J Shanghai Jiaotong Univ Sci    2023, 28 (4): 411-.   DOI: 10.1007/s12204-022-2481-y Abstract （318）      PDF（pc） （1220KB）（99）       Knowledge map    Save Precise temperature control and temperature distribution prediction are of great significance forradiofrequency ablation. This research proposes a real-time calculation method for the temperature distribution of radiofrequency ablation combined with proportional-integral temperature control. The thermo-electricalcoupling was simplified into a linear relationship based on the study of the influence of temperature-dependentelectrical conductivity and thermal conductivity on the PI-controlled radiofrequency ablation temperature distribution, which increases the computational efficiency by 150 times. The average calculation time for radiofrequencyablation of 10 min is about 23 s, and the difference between the calculation results of this method and that fromCOMSOL Multiphysics is no more than 1 ?C. This method is not only used for single-probe, but also for doubleprobe radiofrequency ablation in this paper. Reference | Related Articles | Metrics | Comments（0）

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Augmented Reality Navigation Using Surgical Guides Versus Conventional Techniques in Pedicle Screw Placement KONG Huiyang1 (孔会扬), WANG Shuyi1 (王殊轶), ZHANG Can2 (张璨), CHEN Zan2, 3 (陈赞) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 10-17.   DOI: 10.1007/s12204-023-2689-5 Abstract （318）      PDF（pc） （1106KB）（28）       Knowledge map    Save The aim of this study was to assess the potential of surgical guides as a complementary tool to augmented reality (AR) in enhancing the safety and precision of pedicle screw placement in spinal surgery. Four trainers were divided into the AR navigation group using surgical guides and the free-hand group. Each group consisted of a novice and an experienced spine surgeon. A total of 80 pedicle screws were implanted. First, the AR group reconstructed the 3D model and planned the screw insertion route according to the computed tomography data of L2 lumbar vertebrae. Then, the Microsoft HoloLensTM 2 was used to identify the vertebral model, and the planned virtual path was superimposed on the real cone model. Next, the screw was placed according to the projected trajectory. Finally, Micron Tracker was used to measure the deviation of screws from the preoperatively planned trajectory, and pedicle screws were evaluated using the Gertzbein-Robbins scale. In the AR group, the linear deviations of the experienced doctor and the novice were (1.59±0.39) mm and (1.73±0.52) mm respectively, and the angle deviations were 2.72◦ ± 0.61◦ and 2.87◦ ± 0.63◦ respectively. In the free-hand group, the linear deviations of the experienced doctor and the novice were (2.88 ± 0.58) mm and (5.25 ± 0.62) mm respectively, and the angle deviations were 4.41◦ ± 1.18◦ and 7.15◦ ± 1.45◦ respectively. Both kinds of deviations between the two groups were significantly different (P < 0.05). The screw accuracy rate was 95% in the AR navigation group and 77.5% in the free-hand group. The results of this study indicate that the integration of surgical guides and AR is an innovative technique that can substantially enhance the safety and precision of spinal surgery and assist inexperienced doctors in completing the surgery. Reference | Related Articles | Metrics | Comments（0）

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Entity Relationship Explanation via Conceptualization XIE Chenhao(谢晨昊), LIANG Jiaqing(梁家卿), XIA Yanghua(肖仰华), HWANG Seung-won J Shanghai Jiaotong Univ Sci    2023, 28 (6): 695-702.   DOI: 10.1007/s12204-021-2394-1 Abstract （309）      PDF（pc） （608KB）（119）       Knowledge map    Save Finding an attribute to explain the relationships between a given pair of entities is valuable in many applications. However, many direct solutions fail, owing to its low precision caused by heavy dependence on text and low recall by evidence scarcity. Thus, we propose a generalization-and-inference framework and implement it to build a system: entity-relationship finder (ERF). Our main idea is conceptualizing entity pairs into proper concept pairs, as intermediate random variables to form the explanation. Although entity conceptualization has been studied, it has new challenges of collective optimization for multiple relationship instances, joint optimization for both entities, and aggregation of diluted observations into the head concepts defining the relationship. We propose conceptualization solutions and validate them as well as the framework with extensive experiments. Reference | Related Articles | Metrics | Comments（0）

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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) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 323-329.   DOI: 10.1007/s12204-023-2581-3 Abstract （308）      PDF（pc） （743KB）（48）       Knowledge map    Save 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. Reference | Related Articles | Metrics | Comments（0）

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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) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 307-311.   DOI: 10.1007/s12204-022-2508-4 Abstract （305）      PDF（pc） （2071KB）（68）       Knowledge map    Save 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. Reference | Related Articles | Metrics | Comments（0）

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Stagewise Training for Hybrid-Distorted Image Restoration HOU Shujuan* (侯舒娟)，ZHU Wenping (朱文萍)，LI Hai (李海) J Shanghai Jiaotong Univ Sci    2023, 28 (6): 793-801.   DOI: 10.1007/s12204-022-2453-2 Abstract （305）      PDF（pc） （1221KB）（76）       Knowledge map    Save Image restoration is the problem of restoring a real degraded image. Previous studies mostly focused on single distortion. However, most of the real images experience multiple distortions, and single distortion image restoration algorithms can not effectively improve the image quality. Moreover, few existing hybrid distortion image restoration algorithms can not deal with single distortion. Therefore, an end-to-end pipeline network based on stagewise training is proposed in this paper. Specifically, the network selects three typical image restoration tasks: denoising, inpainting, and super resolution. The whole training process is divided into single distortion training, hybrid distortion training of two types, and hybrid distortion training of three types. The design of loss function draws on the idea of deep supervision. Experimental results prove that the proposed method is not only superior to other methods in hybrid-distorted image restoration, but also suitable for single distortion image restoration. Reference | Related Articles | Metrics | Comments（0）

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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) J Shanghai Jiaotong Univ Sci    2023, 28 (3): 348-359.   DOI: 10.1007/s12204-023-2580-4 Abstract （304）      PDF（pc） （909KB）（36）       Knowledge map    Save 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. Reference | Related Articles | Metrics | Comments（0）

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Transfer Learning in Motor Imagery Brain Computer Interface: A Review LI Mingai1,2,3∗ (李明爱), XU Dongqin1 (许东芹) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 37-59.   DOI: 10.1007/s12204-022-2488-4 Abstract （304）      PDF（pc） （1734KB）（265）       Knowledge map    Save Transfer learning, as a new machine learning methodology, may solve problems in related but different domains by using existing knowledge, and it is often applied to transfer training data from another domain for model training in the case of insufficient training data. In recent years, an increasing number of researchers who engage in brain-computer interface (BCI), have focused on using transfer learning to make most of the available electroencephalogram data from different subjects, effectively reducing the cost of expensive data acquisition and labeling as well as greatly improving the learning performance of the model. This paper surveys the development of transfer learning and reviews the transfer learning approaches in BCI. In addition, according to the “what to transfer” question in transfer learning, this review is organized into three contexts: instance-based transfer learning, parameter-based transfer learning, and feature-based transfer learning. Furthermore, the current transfer learning applications in BCI research are summarized in terms of the transfer learning methods, datasets, evaluation performance, etc. At the end of the paper, the questions to be solved in future research are put forward, laying the foundation for the popularization and in-depth research of transfer learning in BCI. Reference | Related Articles | Metrics | Comments（0）

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Parameter Optimization and Precision Enhancement of Dual-Coil Eddy Current Sensor ZHANG Zhenning1(张振宁)，LIU Qiang2(刘强), Lü Chunfeng3(吕春峰)，MAO Yimeil(毛义梅)，TAo Weil(陶卫),ZHAO Huil*(赵辉) J Shanghai Jiaotong Univ Sci    2023, 28 (5): 596-603.   DOI: 10.1007/s12204-022-2511-9 Abstract （304）      PDF（pc） （948KB）（122）       Knowledge map    Save To enhance the measurement precision of eddy current sensor in particular environments such as extreme temperature changes and limited available space in aerospace, we optimized the structural parameters of the traditional dual-coil eddy current sensor probe by electromagnetic field analysis and finite element simulation modeling, and further presented the criteria for determining the optimal coil distance of the dual-coil probe. The simulation results are verified by setting up an experimental platform. For the extreme temperature environment, the displacement measurement error caused by the full range temperature variation of the dual-coil sensor under the optimal distance is less than 21.0% of that of the single-coil sensor. On this basis, we analyzed and verified the thermal stability of the structurally optimized dual-coil eddy current sensor. After temperature compensation, the displacement measurement accuracy can reach 14.9 times more accurate than that of the single-coil sensor. The method proposed in this paper can provide a design reference for the structural optimization of the axial dual-coil eddy current sensor probe. Reference | Related Articles | Metrics | Comments（0）

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Anti-Occlusion Object Tracking Algorithm Based on Filter Prediction CHEN Kun(陈坤), ZHAO Xu(赵旭), DONG Chunyu(董春玉), DI Zichao(邸子超), CHEN Zongzhi(陈宗枝) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 400-413.   DOI: 10.1007/s12204-022-2484-8 Abstract （301）      PDF（pc） （5510KB）（92）       Knowledge map    Save Visual object tracking is an important issue that has received long-term attention in computer vision.The ability to effectively handle occlusion, especially severe occlusion, is an important aspect of evaluating theperformance of object tracking algorithms in long-term tracking, and is of great significance to improving therobustness of object tracking algorithms. However, most object tracking algorithms lack a processing mechanism specifically for occlusion. In the case of occlusion, due to the lack of target information, it is necessary to predict the target position based on the motion trajectory. Kalman filtering and particle filtering can effectively predict the target motion state based on the historical motion information. A single object tracking method, called probabilistic discriminative model prediction (PrDiMP), is based on the spatial attention mechanism in complex scenes and occlusions. In order to improve the performance of PrDiMP, Kalman filtering, particle filtering and linear filtering are introduced. First, for the occlusion situation, Kalman filtering and particle filtering are respectively introduced to predict the object position, thereby replacing the detection result of the original tracking algorithm and stopping recursion of target model. Second, for detection-jump problem of similar objects in complex scenes, a linear filtering window is added. The evaluation results on the three datasets, including GOT-10k, UAV123 and LaSOT, and the visualization results on several videos, show that our algorithms have improved tracking performance under occlusion and the detection-jump is effectively suppressed. Reference | Related Articles | Metrics | Comments（0）

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Performance and Optimization of Air Source Heat Pump Water Heater with Cyclic Heating LI Fan(李凡), LU Gaofeng(陆高锋), DING Yunxiao(丁云霄), ZHENG Chunyuan(郑春元), LI Bin(李斌), ZHAI Xiaoqiang(翟晓强) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 179-187.   DOI: 10.1007/s12204-022-2500-z Abstract （295）      PDF（pc） （1349KB）（74）       Knowledge map    Save A new type of microchannel condenser applied in the air source heat pump water heater (ASHPWH) with cyclic heating was proposed in this study. The operating performance of the ASHPWH was first tested. Then,the structure of the microchannel condenser was optimized with the implement of vortex generators. Finally, a numerical model of the ASHPWH was established and the optimized microchannel condenser was studied. The experimental results showed that the average coefficient of performance (COP) of the 1 HP (735 W) ASHPWH reached 3.48. In addition, the optimized microchannel condenser could be matched with a 3 HP (2 430 W) ASHPWH with an average heating capacity of 10.30 kW, and achieving an average COP of 4.24, 14.6% higher than the limit value in the national standard. Reference | Related Articles | Metrics | Comments（0）

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A Novel Cable-Driven Soft Robot for Surgery LI Ru1 (李茹), CHEN Fang2 (陈方), YU Wenwei3 (俞文伟), IGARASH Tatsuo3,4, SHU Xiongpeng1 (舒雄鹏), XIE Le1,5,6∗ (谢叻) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 60-72.   DOI: 10.1007/s12204-022-2497-3 Abstract （292）      PDF（pc） （2939KB）（171）       Knowledge map    Save Robot-assisted laparoscopic radical prostatectomy (RARP) is widely used to treat prostate cancer. The rigid instruments primarily used in RARP cannot overcome the problem of blind areas in surgery and lead to more trauma such as more incision for the passage of the instrument and additional tissue damage caused by rigid instruments. Soft robots are relatively flexible and theoretically have infinite degrees of freedom which can overcome the problem of the rigid instrument. A soft robot system for single-port transvesical robot-assisted radical prostatectomy (STvRARP) is developed in this study. The soft manipulator with 10 mm in diameter and a maximum bending angle of 270? has good flexibility and dexterity. The design and mechanical structure of the soft robot are described. The kinematics of the soft manipulator is established and the inverse kinematics is compensated based on the characteristics of the designed soft manipulator. The master-slave control system of soft robot for surgery is built and the feasibility of the designed soft robot is verified. Reference | Related Articles | Metrics | Comments（0）

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CT Image Segmentation Method of Composite Material Based on Improved Watershed Algorithm and U-Net Neural Network Model XUE Yongboa (薛永波)，LIU Zhaob (刘钊)， LI Zeyanga (李泽阳)，ZHU Pinga* (朱平) J Shanghai Jiaotong Univ Sci    2023, 28 (6): 783-792.   DOI: 10.1007/s12204-021-2385-2 Abstract （290）      PDF（pc） （1655KB）（60）       Knowledge map    Save In the study of the composite materials performance, X-ray computed tomography (XCT) scanning has always been one of the important measures to detect the internal structures. CT image segmentation technology will effectively improve the accuracy of the subsequent material feature extraction process, which is of great significance to the study of material performance. This study focuses on the low accuracy problem of image segmentation caused by fiber cross-section adhesion in composite CT images. In the core layer area, area validity is evaluated by morphological indicator and an iterative segmentation strategy is proposed based on the watershed algorithm. In the transition layer area, a U-net neural network model trained by using artificial labels is applied to the prediction of segmentation result. Furthermore, a CT image segmentation method for fiber composite materials based on the improved watershed algorithm and the U-net model is proposed. It is verified by experiments that the method has good adaptability and effectiveness to the CT image segmentation problem of composite materials, and the accuracy of segmentation is significantly improved in comparison with the original method, which ensures the accuracy and robustness of the subsequent fiber feature extraction process Reference | Related Articles | Metrics | Comments（0）

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Ship Pipe Layout Optimization Based on Improved Particle Swarm Optimization LIN Yan1, 2(林焰), BIAN Xuanyi1(卞璇屹), DONG Zongran3(董宗然) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 737-746.   DOI: 10.1007/s12204-022-2530-6 Abstract （286）      PDF（pc） （1456KB）（102）       Knowledge map    Save Ship pipe layout optimization is one of the difficulties and hot spots in ship intelligent production design. A high-dimensional vector coding is proposed based on the research of related pipe coding and ship pipe route features in this paper. The advantages of this coding method are concise structure, strong compatibility, and independence from the gridding space. Based on the proposed coding, the particle swarm optimization algorithm is implemented, and the algorithm is improved by the pre-selected path strategy and the branch-pipe processing strategy. Finally, two simulation results reveal that the proposed coding and algorithm have feasibility and engineering practicability. Reference | Related Articles | Metrics | Comments（0）

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Positional Information is a Strong Supervision for Volumetric Medical Image Segmentation ZHAO Yinjie1 (赵寅杰), HOU Runpingg1 (侯润萍), ZENG Wanqin2 (曾琬琴), QIN Yulei1 (秦玉磊), SHEN Tianle2 (沈天乐), XU Zhiyong2 (徐志勇), FU Xiaolong2* (傅小龙), SHEN Hongbin1* (沈红斌) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 121-129.   DOI: 10.1007/s12204-023-2614-y Abstract （285）      PDF（pc） （481KB）（4）       Knowledge map    Save Medical image segmentation is a crucial preliminary step for a number of downstream diagnosis tasks. As deep convolutional neural networks successfully promote the development of computer vision, it is possible to make medical image segmentation a semi-automatic procedure by applying deep convolutional neural networks to finding the contours of regions of interest that are then revised by radiologists. However, supervised learning necessitates large annotated data, which are difficult to acquire especially for medical images. Self-supervised learning is able to take advantage of unlabeled data and provide good initialization to be finetuned for downstream tasks with limited annotations. Considering that most self-supervised learning especially contrastive learning methods are tailored to natural image classification and entail expensive GPU resources, we propose a novel and simple pretext-based self-supervised learning method that exploits the value of positional information in volumetric medical images. Specifically, we regard spatial coordinates as pseudo labels and pretrain the model by predicting positions of randomly sampled 2D slices in volumetric medical images. Experiments on four semantic segmentation datasets demonstrate the superiority of our method over other self-supervised learning methods in both semisupervised learning and transfer learning settings. Codes are available at https://github.com/alienzyj/PPos. Reference | Related Articles | Metrics | Comments（0）

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Adjacent Segment Biomechanical Changes After Implantation of Cage Plus Plate or Zero-Profile Device in Different Segmental Anterior Cervical Discectomy and Fusion YE Peng (叶鹏), FU Rongchang∗ (富荣昌), WANG Zhaoyao (王召耀) J Shanghai Jiaotong Univ Sci    2025, 30 (1): 166-174.   DOI: 10.1007/s12204-023-2633-8 Abstract （284）      PDF（pc） （929KB）（18）       Knowledge map    Save Cage plus plate (CP) and zero-profile (Zero-P) devices are widely used in anterior cervical discectomy and fusion (ACDF). This study aimed to compare adjacent segment biomechanical changes after ACDF when using Zero-P device and CP in different segments. First, complete C1—C7 cervical segments were constructed and validated. Meanwhile, four surgery models were developed by implanting the Zero-P device or CP into C4—C5 or C5—C6 segments based on the intact model. The segmental range of motion (ROM) and maximum value of the intradiscal pressure of the surgery models were compared with those of the intact model. The implantation of CP and Zero-P devices in C4—C5 segments decreased ROM by about 91.6% and 84.3%, respectively, and increased adjacent segment ROM by about 8.3% and 6.82%, respectively. The implantation of CP and Zero-P devices in C5—C6 segments decreased ROM by about 93.3% and 89.9%, respectively, while increasing adjacent segment ROM by about 4.9% and 4%, respectively. Furthermore, the implantation of CP and Zero-P devices increased the intradiscal pressure in the adjacent segments of C4—C5 segments by about 4.5% and 6.7%, respectively. The implantation of CP and Zero-P devices significantly increased the intradiscal pressure in the adjacent segments of C5—C6 by about 54.1% and 15.4%, respectively. In conclusion, CP and Zero-P fusion systems can significantly reduce the ROM of the fusion implant segment in ACDF while increasing the ROM and intradiscal pressure of adjacent segments. Results showed that Zero-P fusion system is the best choice for C5—C6 segmental ACDF. However, further studies are needed to select the most suitable cervical fusion system for C4—C5 segmental ACDF. Therefore, this study provides biomechanical recommendations for clinical surgery. Reference | Related Articles | Metrics | Comments（0）

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Time-Resolved Imaging in Short-Wave Infrared Region XU Yang (徐杨), LI Wanwan∗ (李万万) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 29-36.   DOI: 10.1007/s12204-022-2547-x Abstract （282）      PDF（pc） （810KB）（58）       Knowledge map    Save Compared with the conventional first near-infrared (NIR-I, 700—900 nm) window, the short-wave infrared region (SWIR, 900—1 700 nm) possesses the merits of the increasing tissue penetration depths and the suppression of scattering background, leading to great potential for in vivo imaging. Based on the limitations of the common spectral domain, and the superiority of the time-dimension, time-resolved imaging eliminates the auto-fluorescence in the biological tissue, thus supporting higher signal-to-noise ratio and sensitivities. The imaging technique is not affected by the difference in tissue composition or thickness and has the practical value of quantitative in vivo detection. Almost all the relevant time-resolved imaging was carried out around lanthanide-doped upconversion nanomaterials, owing to the advantages of ultralong luminescence lifetime, excellent photostability, controllable morphology, easy surface modification and various strategies of regulating lifetime. Therefore, this review presents the research progress of SWIR time-resolved imaging technology based on nanomaterials doped with lanthanide ions as luminescence centers in recent years. Reference | Related Articles | Metrics | Comments（0）

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Psychological Impact of the 2022 Round COVID-19 Pandemic on China’s College Students HONG Dongyang1,3 (洪冬羊), WANG Jinxia2,3 (王金霞), ZHANG Hongyang2,3 (张虹洋), CAO Ziyang2,3 (曹紫阳), YAN Zijun 2,3 (晏紫君), ZOU Lin2,3∗ (邹琳) J Shanghai Jiaotong Univ Sci    2024, 29 (1): 141-149.   DOI: 10.1007/s12204-022-2557-8 Abstract （282）      PDF（pc） （194KB）（31）       Knowledge map    Save In response to the new round of COVID-19 outbreaks since March 2022, universities with high outbreak rates around the country have taken quarantine measures to contain the epidemic. Evidence from previous coronavirus outbreaks has shown that people under quarantine are at risk for mental health disorders. To better understand the impacts of this round of COVID-19 quarantine on domestic college students and their responses, we conducted a systematic survey to assess the stress and anxiety, and to evaluate effective measurements in this population. We searched relevant documents and literature, and designed a questionnaire from six aspects, including psychological status, epidemic situation, study, daily life, sports, and interpersonal communication, with 51 items in total. We sent the questionnaire on the Wenjuanxing Web platform, from April 2 to 8, 2022. We evaluated the mental status according to parts of the Generalized Anxiety Disorder-7 (GAD-7) and Depression Anxiety Stress Scales-21 (DASS-21), and investigated the influencing risk factors and countermeasures. Statistical analysis was performed by using the Chi-square test and multi-variable logistic regression. In total, 508 college respondents were recruited in our survey, and the pooled prevalence of mild anxiety (GAD score  5, or DASS-21 anxiety score 8) or stress (DASS-21 pressure score 14) caused by the new round of COVID-19 pandemic quarantine was 19.69% (100/508). The prevalence of the anxiety or stress in college students with COVID-19 quarantine between different genders, regions, and majors was not significantly different. Independent risk factors for the mild anxiety or stress of undergraduates by COVID-19 quarantine included learning efficiency or duration [OR = 1.36, 95%CI (1.14—1.62), P = 0.001], based on the combined analysis of Chi-square test analysis with multi-variable logistic regression analysis. Interestingly, the mental well-beings before COVID-19 epidemic quarantine [OR = 0.22, 95%CI (0.13—0.36), P < 0.000 1], more low-intensity exercise [OR = 0.36, 95%CI (0.15—0.87), P = 0.02, high-intensity exercise as reference], and good sleep quality [OR = 0.14, 95%CI (0.07—0.30), P < 0.000 1: OR = 0.42, 95%CI (0.30—0.59), P < 0.000 1] are protective factors for alleviating the quarantinecaused anxiety or stress in Chinese college students for this round of COVID-19 epidemic quarantine. During the round of COVID-19 epidemic quarantine in 2022, a small number of college students have mild anxiety, affected by decreased learning efficiency or duration, which could be mitigated with low-intensity exercise and good sleep quality. Reference | Related Articles | Metrics | Comments（0）