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A Pilot Study on Fabric-based Pneumatic Soft Gloves for Assisting Patients with Severe Brachial Plexus Injury

IEEE Transactions on Biomedical engineering 2025年 PP卷 PP页

作者： Feng, Miao Yang, Dezhi Sun, Jianing Lao, Jie Rui, Jing Gu, Guoying Shanghai Jiao Tong University Robotics Institute State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Key Laboratory of Intelligent Robotics Meta Robotics Institute Shanghai200240 China Southwest Technology and Engineering Research Institute Chongqing400039 China Fudan University Department of Hand Surgery Huashan Hospital China NHC Key Laboratory of Limbs Reconstruction Shanghai Key Laboratory of Peripheral Nerve and Microsurgery Shanghai200040 China

Objective: Robotic gloves show promise in hand assistance due to their wearability and home-based potential, yet empirical research remains limited. This pilot study presents a fabric-based pneumatic soft glove, aiming to identify its potential and challenges in clinical practice by evaluating its effectiveness in assisting patients with severe brachial plexus injury (BPI). Methods: The glove integrates a thumb abduction actuator and four bidirectional fabric-based pneumatic actuators (FPAs) with asymmetric chambers for high output force. Sixteen healthy volunteers and five individuals with BPI, all of whom lacked active hand and wrist movements, were recruited. Participants performed object grasping across 25 cm. The healthy group performed seven tasks using objects weighing up to 2 kg, with muscle activities recorded for analysis. The BPI group further performed tasks with eight objects from the action research arm test (ARAT) and twelve objects for activities of daily living (ADLs), encompassing various sizes, weights, and geometries. Results: In the healthy group, sEMG showed a decrease in 89.3% of trials, with 56.0% of these decreases being significant (p © 1964-2012 IEEE.

关键词： Pneumatic actuators

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Design and Development of an Armadillo-Inspired Robot With Multiple Locomotion Modes

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IEEE/ASME Transactions on Mechatronics 2025年

作者： Zhang, Ziqiang Wu, Qicai Liao, Jinnong Beijing University of Technology School of Mechanical and Energy Engineering Beijing100124 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

The diversification of locomotion modes can expand the movement range of mobile robots, and enhance their adaptability to complex environments. While the combination of two locomotion modes is quite common, there is still considerable scope for enhancing the environmental adaptability of such robots. In this article, an armadillo-inspired robot (AIRO) with two motion modes, crawling, and rolling, is designed and developed. According to the proposed mechanism design method based on layered constraints, a one-degree of freedom six-bar trunk mechanism is designed and evaluated according to the kinematic chain and the actual configurations, which can realize the switching between crawling and rolling modes with only one motor, and has the advantages of simple control and high structural stiffness, and then the C-shaped arc legs are designed to satisfy the kinematic requirements. Finally, a single/multiple motion modes performance score formula is proposed to quantitatively evaluate the robot's mobility performance based on the indexes such as stability, energy consumption, and speed. The developed prototype of AIRO weighs 2.35 kg and has a maximum size of 469.6 mm × 246.6 mm × 143.2 mm. Experimental results demonstrate that AIRO achieves a maximum crawling speed of 0.192 m/s and a maximum rolling speed of 0.464 m/s on flat terrain, which provides good adaptability to complex terrain. The research results provide a reference for the development of similar robots with multiple motion modes. © 1996-2012 IEEE.

关键词： Mobile robots

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Study on wear mechanism of small ball-end grinding wheel and surface integrity of complex component under high-speed machining condition

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Wear 2025年

作者： Qin, Biao Liu, Henan Cheng, Jian Tian, Jinchuan Sun, Jiangang Chen, Mingjun School of Mechatronics Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou450000 China

The small ball-end fine diamond grinding wheel is well-suited for machining complex components with small curved surface structures, demonstrating high-precision and high-quality machining capabilities. By increasing the speed of the workpiece, the issue of poor grinding performance caused by the small diameter of the ball-end grinding wheel can be effectively overcome. However, this strategy inevitably increases wheel wear and affects surface integrity. To address these challenges, this paper systematically investigates the grinding characteristics of the small ball-end grinding wheel. First, grinding experiments were performed to investigate the influence of workpiece speed, feed rate, and grinding depth on the material removal rate, wheel wear, and surface integrity. Then, the wear mechanism of the grinding wheel was analyzed. The wear modes of the grinding wheel at high workpiece speeds include metal adhesive wear and abrasive grain fracture, which enhance the self-sharpening of the grinding wheel while accelerating its wear. Furthermore, the surface morphology creation mechanism of fused silica under different material removal modes was revealed. Moreover, the correlation between material removal rate and surface roughness caused by wheel wear was revealed. A high-speed grinding strategy was subsequently proposed based on the relationship between the grinding characteristics and grinding parameters of the small ball-end grinding wheel under various grinding conditions. Finally, the feasibility of this grinding strategy was validated through its application to the machining of the complex curved fused silica hemispherical resonator (HSR). Experimental results indicate that under the high workpiece speed condition, the best surface roughness of HSR decreases from 90.5 nm to 62.2 nm, while the maximum grinding wheel wear increases from 9.7 μm to 11.5 μm, with minimal impact on surface integrity. Therefore, the high-speed grinding strategy proposed in this study ho

关键词： Fused silica

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Design of a SMA actuated freeplay elimination device for stiffness enhancement of a folding fin

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Mechanical systems and Signal Processing 2025年 234卷

作者： Zhang, Rongru Chen, Gang Yue, Honghao Si, Mingyu State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin 150001 China Beijing Institute of Electronic System Engineering Beijing 100854 China

The folding fin, essential for controlling aircraft flight attitude and maintaining stability, is extensively employed in aerospace vehicles. Inevitable freeplay within the structure, due to design, installation, and mechanical wear, reduce the stiffness of the folding fins and impair the aircraft's aerodynamic performance. Therefore, eliminating the freeplay in the folding fin is crucial for enhancing the aircraft's flight accuracy and stability. This paper introduces a novel freeplay elimination device utilizing SMA columns, which neither increases mass nor alters the aircraft's external dimensions. The device effectively alleviates nonlinear issues associated with gaps in the fin system and enhances both the dynamic and static stiffness of the folding fin. A parametric design model for the gap elimination device has been developed, delineating the relationship between the structure and layout of the SMA columns, the actuation temperature, load, and the target gap for elimination. We conducted static load tests along with modal tests at room and elevated temperatures to evaluate the stiffness enhancement performance of the folding fin before and after gap elimination. The experiments verified that the designed gap elimination device significantly enhances both the static and dynamic stiffness of the folding fin. Additionally, the first-order frequency of the folding fin increased by 40 % at room temperature and by 36.7 % at 200 °C. This paper provides quantifiable guidance for the structural and parametric design of gap elimination devices in folding fins. Optimal structural parameters, determined based on aerodynamic loads and gap elimination requirements, enhance the stiffness of the folding fin, thus improving the aircraft's flight performance. © 2025

关键词： Actuator Folding fin Freeplay SMA Stiffness enhancement

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Muscle Activation Estimation by Optimizing the Musculoskeletal Model for Personalized Strength and Conditioning Training

arXiv

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arXiv 2025年

作者： Wu, Xi Li, Chenzui Zou, Kehan Xi, Ning Chen, Fei Department of Mechanical and Automation Engineering T-Stone Robotics Institute The Chinese University of Hong Kong Hong Kong Department of Industrial and Manufacturing System Engineering The University of Hong Kong Hong Kong

Musculoskeletal models are pivotal in the domains of rehabilitation and resistance training to analyze muscle conditions. However, individual variability in musculoskeletal parameters and the immeasurability of some internal biomechanical variables pose significant obstacles to accurate personalized modelling. Furthermore, muscle activation estimation can be challenging due to the inherent redundancy of the musculoskeletal system, where multiple muscles drive a single joint. This study develops a whole-body musculoskeletal model for strength and conditioning training and calibrates relevant muscle parameters with an electromyography-based optimization method. By utilizing the personalized musculoskeletal model, muscle activation can be subsequently estimated to analyze the performance of exercises. Bench press and deadlift are chosen for experimental verification to affirm the efficacy of this approach. Copyright © 2025, The Authors. All rights reserved.

关键词： Electromyography

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Deep reinforcement learning-based trajectory planning for double pendulum cranes: Design and experiments

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Mechanical systems and Signal Processing 2025年 234卷

作者： Ding, Weili Zhang, Heng Hua, Changchun Lu, Biao Engineering Research Center of Intelligent Control System and Intelligent Equipment Ministry of Education Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Institute of Electrical Engineering Yanshan University Qinhuangdao066004 China Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300353 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

Since cranes usually possess double pendulum dynamics, the mass of the payload often changes and there are frequently lifting/lowering operations simultaneously. Moreover, most crane systems are driven by motors, whose velocities and accelerations are often limited. To solve the above problems, this paper proposes a deep reinforcement learning (DRL) reference trajectory generation method based on virtual–physical joint training. Firstly, a DRL module based on deep deterministic policy gradient (DDPG), along with a double pendulum crane dynamic model and an adaptive controller, are established within the virtual environment for training the reference trajectory. When the reward reaches the threshold, the training is switched to the physical environment to further optimize the reference trajectory, realizing the swing suppression of the hook and the payload. In addition, to satisfy the performance of the drive motors, velocity and acceleration thresholds are set to constrain the performance of the drive motors. Finally, in view of the fact that the operation process of the double pendulum crane is divided into payload transportation and payload loading/unloading, an event-triggering mechanism is designed to switch different control policies in accordance with different operation processes, thus reducing the consumption of computing resources. Through experiments on the actual double pendulum crane and comparison with the existing reference trajectories and input shapers, the superiority of this method is demonstrated. © 2025 Elsevier Ltd

关键词： Model reference adaptive control

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Complete Gait Phase Recognition Based on Muscle Synergy Using PSO-CNN-LSTM Algorithm

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IEEE Sensors Journal 2025年第10期25卷 16775-16786页

作者： Zhang, Kewen Li, Xiaoling Chen, Xin Yu, Longjie Jin, Yinan Fan, Bingfei Du, Mingyu Bao, Guanjun Wu, Xinyu Cai, Shibo Zhejiang University of Technology College of Mechanical Engineering Key Laboratory of Special Purpose Equipment and Advanced Processing Technology Ministry of Education and Zhejiang Province Hangzhou310023 China Zhejiang University of Technology College of Mechanical Engineering Hangzhou310023 China ZJUT Yinhu Research Institute of Innovation and Entrepreneurship Zhejiang University of Technology Fuyang Hangzhou310023 China Shenzhen Institutes of Advanced Technology Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen518055 China

Accurately recognizing gait phases, by applying proper instrumentation and measurement, is significant in walking rehabilitation training for patients with impaired mobility. In this study, seven phases of complete stand-walk–stand cycle as well as continuous daily walking were recognized based on muscle synergy and particle swarm optimization (PSO)-convolutional neural network (CNN)-long short-term memory (LSTM) model. First, the complete stand-walk–stand walking cycle was divided into starting phase, terminal swing phase, loading response phase, mid-stance phase, terminal stance phase, initial swing phase, and stopping phase, based on the features of surface electromyography (sEMG) collected by portable sEMG acquisition system and measured motion data of lower limb. Second, a muscle weight matrix and an activation sequence matrix were calculated by using nonnegative matrix factorization (NMF). Finally, a PSO-CNN-LSTM network was designed to recognize the complete stand-walk–stand cycle by applying the abovementioned matrices as input. Fourteen subjects volunteered to perform linear walking experiments under procedure to verify the feasibility of the proposed approach by comparing results with other classifiers and features. Experimental results show that the proposed approach was capable of achieving an average recognition accuracy of up to 85.384%. This work will offer a promising gait recognition method for rehabilitation robots to achieve natural and flexible human-robot interaction. © 2001-2012 IEEE.

关键词： Non-negative matrix factorization

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Domain-Adaptive Power Profiling Analysis Strategy for the Metaverse

Domain-Adaptive Power Profiling Analysis Strategy for the Me...

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作者： Li, Xiang Yang, Ning Liu, Weifeng Chen, Aidong Zhang, Yanlong Wang, Shuo Zhou, Jing Beijing Key Laboratory of Information Service Engineering Beijing Union University Beijing China Institute of Semiconductors Chinese Academy of Sciences Beijing China College of Robotics Beijing Union University Beijing China Research Center for Multi-Intelligent Systems Beijing Union University Beijing China Information System Laboratory Beijing Microelectronics Technology Institution Beijing China

In the surge of the digital era, the metaverse, as a groundbreaking concept, has become a focal point in the technology sector. It is reshaping human work and life patterns, carving out a new realm of virtual and real interaction. However, the rapid development of the metaverse brings along novel challenges in security and privacy. In this multifaceted and complex technological environment, data protection is of paramount importance. The innovative capabilities of high-end devices and functions in the metaverse, owing to advanced integrated circuit technology, face unique threats from side-channel analysis (SCA), potentially leading to breaches in user privacy. Addressing the issue of domain differences caused by different hardware devices, which impact the generalizability of the analysis model and the accuracy of analysis, this paper proposes a strategy of portability power profiling analysis (PPPA). Combining domain adaptation and deep learning techniques, it models and calibrates the domain differences between the profiling and target devices, enhancing the model's adaptability in different device environments. Experiments show that our method can recover the correct key with as few as 389 power traces, effectively recovering keys across different devices. This paper underscores the effectiveness of cross-device SCA, focusing on the adaptability and robustness of analysis models in different hardware environments, thereby enhancing the security of user data privacy in the metaverse environment. © 2024 John Wiley & Sons Ltd.

关键词： Data privacy

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NavG: Risk-Aware Navigation in Crowded Environments Based on Reinforcement Learning with Guidance Points

arXiv

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arXiv 2025年

作者： Zhang, Qianyi Luo, Wentao Liu, Boyi Zhang, Ziyang Wang, Yaoyuan Liu, Jingtai Institute of Robotics and Automatic Information System Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin China Advanced Computing and Storage Lab Huawei 2012 Lab China Department of Electronic and Computer Engineering The Kong Kong University of Science and Technology Hong Kong

Motion planning in navigation systems is highly susceptible to upstream perceptual errors, particularly in human detection and tracking. To mitigate this issue, the concept of guidance points—a novel directional cue within a reinforcement learning-based framework—is introduced. A structured method for identifying guidance points is developed, consisting of obstacle boundary extraction, potential guidance point detection, and redundancy elimination. To integrate guidance points into the navigation pipeline, a perception-to-planning mapping strategy is proposed, unifying guidance points with other perceptual inputs and enabling the RL agent to effectively leverage the complementary relationships among raw laser data, human detection and tracking, and guidance points. Qualitative and quantitative simulations demonstrate that the proposed approach achieves the highest success rate and near-optimal travel times, greatly improving both safety and efficiency. Furthermore, real-world experiments in dynamic corridors and lobbies validate the robot’s ability to confidently navigate around obstacles and robustly avoid pedestrians. © 2025, CC BY.

关键词： Travel time

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Exploring Eye-tracking based Biomarkers to Assess Cognitive Abilities in Autistic Children: A Feasibility Study

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Zhang, Hanlin Hu, Chunchun Wang, Zhiyong Zhou, Bingrui Wang, Xinming Nie, Wei Ye, Qinyi Lin, Ruihan Xu, Xiu Liu, Honghai Children's Hospital of Fudan University Department of Child Health Care Shanghai201102 China Harbin Institute of Technology State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Shenzhen518055 China Peng Cheng Laboratory Shenzhen518000 China

Cognitive assessment can reveal a person's cognitive processing and behavioral patterns, making it an indispensable component of autism intervention and prognosis. Existing machine-assisted cognitive assessment methods primarily focus on children's performance outcomes, overlooking distinctive behavioral models, particularly characteristics of eye movement behavior, which have been demonstrated as the most direct indicators of cognitive abilities. In this study, we explore eye-tracking biomarkers for assisting cognitive assessment through a series of meticulously designed multi-level human-computer interaction protocols, encompassing three cognitive abilities: pairing and categorization, emotion recognition, and social interaction. A platform embedded with an eye-tracking module has been developed to reliably collect and analyze eye movement data, even in the presence of unrestricted large head movements in children. Experimental results indicate that there are significant group differences between autism and typically developing children in the eye-tracking features of total fixation duration, response latency, time to first fixation, mean fixation duration, and visit count in the absence of significant intergroup differences in the Wechsler Preschool and Primary Scale of Intelligence (WPPSI) and Wechsler Intelligence Scale for Children (WISC) assessment results. In addition, certain eye movement features in each group are correlated with WPPSI/WISC scale scores, enabling clinical cognitive assessments within each group based on these eye movement features. This study suggests that using eye-tracking features as biomarkers to assist detailed cognitive assessments holds significant potential for the intervention and prognosis of autism. © 2013 IEEE.

关键词： Diseases

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