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Assessing Sarcopenia-Prone Risk through Daily Activity of Gait With AI-Powered Wearable IoT Sensors

IEEE Internet of Things Journal 2025年第12期12卷 20301-20313页

作者： Zhang, Hongyu Wang, Keer Cheng, Clio Yuen Man Chen, Meng Lai, King Wai Chiu Or, Calvin Kalun Hu, Yong Vellaisamy, Arul Lenus Roy Lam, Cindy Lo Kuen Xi, Ning Lou, Vivian W. Q. Li, Wen Jung City University of Hong Kong Department of Mechanical Engineering Hong Kong Hong Kong The University of Hong Kong Department of Social Work and Social Administration Sau Po Centre on Ageing Hong Kong Hong Kong City University of Hong Kong Centre for Robotics and Automation Department of Biomedical Engineering Hong Kong Hong Kong The University of Hong Kong Department of Industrial and Manufacturing System Engineering Hong Kong Hong Kong The University of Hong Kong Li Ka Shing Faculty of Medicine Department of Orthpedics and Traumatology Hong Kong Hong Kong Hong Kong Metropolitan University School of Science and Technology Hong Kong Hong Kong The University of Hong Kong Li Ka-Shing Faculty of Medicine Department of Family Medicine and Primary Care Hong Kong Hong Kong

Sarcopenia is a progressive condition characterized by age-related losses in muscle mass and strength, and irreversible in its advanced stages. While sarcopenia negatively impacts daily living, accurately, quickly and economically assessing its effects can be challenging due to individual variability in activity levels. This study introduced a novel approach for assessing the risk of sarcopenia-prone using machine learning and wearable IoT (Internet of Things) sensors. A total of 53 community-dwelling older adults aged 65+ underwent gait analysis using dual sensors. Nineteen gait features were extracted from each cycle and used to train classification algorithms to categorize participants as healthy, risk level 1, risk level 2, or risk level 3 for sarcopenia. Binary classification of healthy vs. sarcopenic-prone achieved 97.41% accuracy on average, while four-class classification averaged 94.67%. Notably, the research discovered worsening gait symmetry with increasing sarcopenia-prone severity. These results indicate IoT sensor-assessed gait may serve as a sensitive indicator for daily sarcopenia-prone screening. Accurate assessment of sarcopenia-prone individuals can be achieved through only a 4-meter walking test, significantly reducing the burden for older adults. This approach offers a cost-effective, convenient, and accurate method for early sarcopenia risk detection and intervention, potentially improving quality of life for older adults. This system could also aid in creating widely applicable monitoring products for assessing sarcopenia risk, supporting IoT, and thereby enabling early identification and intervention for individuals at risk of this condition. © 2014 IEEE.

关键词： Risk assessment

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The shape optimization design of the guide plate of the modular AUV recovery device 6

The shape optimization design of the guide plate of the modu...

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6th International Conference on automation, Control and robotics engineering, CACRE 2021

作者： Wang, Xuhui Zhang, Wei Lin, Yang Gu, Haitao Meng, Lingshuai Gao, Dongyong School of Mechanical Engineering and Automation Northeastern University Shenyang China Naval Research Academy Beijng China State Key Laboratory of Robotics Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China College of Mechanical Engineering Shenyang University of Technology Shenyang China

ISBN: (纸本)9781665435765

At present, the main method of ocean exploration is Autonomous Underwater Vehicle (AUV) in cooperation with manned Vehicles. After AUV completes its mission, it relies on the operator to retrieve it on the deck of the Vehicle. This recycling method has shortcomings such as low work efficiency and high personnel risk. In order to meet the development needs of AUV applications in the future, it is urgent to carry out research on AUV independent recycling technology. In this paper, a modular AUV autonomous recovery device based on the Unmanned Surface Vehicle (USV) platform is designed in conjunction with the SEA-KET autonomous AUV recovery method. In order to improve the success rate and efficiency of AUV docking, reduce recovery time, and optimize the collision force in the docking process, the guide plate in the recovery device is optimized and designed. The shape of the guide plate is obtained by combination optimization, and the guiding ability of the optimized guide plate is compared with the conventional shape guide plate, which verifies the validity and reliability of the optimization result. © 2021 IEEE.

关键词： Autonomous underwater vehicles

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Tracking Error Boundary of Novel Stable Inversion Based Feedforward Control for a Class of Non-minimum Phase Systems 5th

Tracking Error Boundary of Novel Stable Inversion Based Fee...

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5th China Conference on Intelligent Networked Things, CINT 2022

作者： Zhu, Shaoqin Wang, Yinpei Zhu, Bin Ji, Xiaoqiang The Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Guangdong Shenzhen China School of Science and Engineering The Chinese University of Hong Kong Guangdong Shenzhen China University of California Irvine United States Department of Automation Tsinghua University Beijing China

ISBN: (纸本)9789811989148

Feedforward control methods enable discrete-time control systems to perform tasks with high tracking performance. Discrete-time systems very often have unstable inverses, with the instability being introduced when producing the discrete analogy of a continuous-time system. The problem statements for two novel stable inverses are given. The aim of this paper is to derive the tracking error bounds realized by the novel stable inversion-based feedforward control, under uncertainties from both measurement noise and model parameters. Simulation results are conducted to justify the validity. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Discrete time control systems

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A Data-driven Feedforward Control Design Method for Nonlinear Systems 5th

A Data-driven Feedforward Control Design Method for Nonline...

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5th China Conference on Intelligent Networked Things, CINT 2022

作者： Li, Luan Zhu, Bin Wang, Yinpei Ji, Xiaoqiang The Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Guangdong Shenzhen China The School of Science and Engineering The Chinese University of Hong Kong Guangdong Shenzhen China Department of Automation Tsinghua University Beijing China University of California Irvine United States

ISBN: (纸本)9789811989148

Feedforward controllers are widely used in industries with high demand for tracking accuracy. Model-based control design methods face modeling difficulty and uncertainty when dealing with increasingly complicated systems. In this paper, we present a new data-driven feedforward control design method. With the assistance of Koopman operator theory, nonlinear systems are lifted to high-dimensional space. Then the inverse of the lifted system is found and a feedforward controller is designed, which can directly work on the original system. Two simulation examples are presented, testifying the efficiency of the proposed method, and the comparison to the generally used local linearization approach is presented. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feedforward control

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IoT Intervention in the monitoring of aquaponics metrics and control of input schedule

IoT Intervention in the monitoring of aquaponics metrics and...

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Smart Devices (ICSD), International Conference on

作者： Pooja Malik Praveen Kumar Malik Gotte Ranjith Kumar Jyoti S. Bali Anshul Mahajan M. Muhsen Hassan School of Electronics and Electrical Engineering Lovely Professional University Phagwara Punjab India School of Computer Science & Artificial Intelligence SR University Warangal Dept of Robotics and Automation Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune The Islamic University Najaf Iraq

ISBN: (数字)9798350394412

ISBN: (纸本)9798350394429

The extensive use of technology across several Modern civilization is clearly impacted by technology, with cutting-edge techniques and tools playing critical roles in sectors including healthcare, business, agriculture, and education. Processes have been transformed by these improvements, which have increased their dependability and efficiency. With the incorporation of technology, agriculture has made enormous strides, with techniques like aquaponics developing as extremely effective and sustainable systems. Aquaponics is a novel farming method that combines hydroponics (soilless plant cultivation) and aquaculture (fish farming) to grow vegetables and fish at the same time. But the performance of this incorporated system relies upon on careful observation of a number of vital elements, such as water high-quality, pH tiers, temperature, and dissolved oxygen levels. To keep the health and growth of both fish and flora in an aquaponics device, it's miles critical to hold perfect situations. This highlights the significance of technological intervention, especially via the integration of Internet of Things (IoT) era, and calls for precision in regulating the input time table for fish feed and plant vitamins.

关键词： Technological innovation Schedules Urban areas Vegetation Water conservation Fish Safety Internet of Things Sustainable development Farming

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Plasma-Enhanced Synthesis of Nitrogen-Doped Silicon Carbide Nanopowders in a Fluidized-Bed Reactor for High-Performance Lithium-Ion Battery Anodes

SSRN

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SSRN 2025年

作者： Wang, Zihao Lei, Zewei Hong, Ruoyu Li, Ming-Lin He, Xianfeng College of Chemical Engineering Fuzhou University Fuzhou350108 China School of Mechanical Engineering and Automation Fuzhou University Fuzhou350108 China International Joint Laboratory on Intelligent Sensing and Robotics Fuzhou University Fuzhou China School of Chemical Engineering University of Chinese Academy of Sciences Beijing101408 China State Key Laboratory of Mesoscience and Engineering Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China

Ultrafine silicon carbide (SiC) powders have garnered increasing attention due to their vast potential for diverse applications. In this study, we developed a plasma-enhanced fluidized bed reactor to crack hexamethyldisilane (HMDS), thereby producing SiC/NC composites with diameters ranging from 10 to 20 nm. This method enables large-scale and sustainable production of SiC/NC composites. Concurrently, nitrogen doping was achieved by introducing ammonia during the plasma process, which increased material defects and thus enhanced electrical conductivity. Moreover, the abundant hydrogen atoms in ammonia modulated the product properties, as evidenced by reduced particle size, enhanced crystallinity, and decreased free-carbon content. The synthesized composites were applied as anodes in lithium-ion batteries, and their feasibility was confirmed through extensive testing. Notably, SiC-150 exhibited a discharge capacity of 413 mAh g-1 after 200 cycles at 0.1 A g-1 and maintained a high specific capacity of 780 mAh g-1 even after 800 cycles at 0.5 A g-1. © 2025, The Authors. All rights reserved.

关键词： Ammonia

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Calibration Method of Industrial Robot Kinematic Parameters Based on Improved SSA Algorithm

Calibration Method of Industrial Robot Kinematic Parameters ...

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Software engineering and Computer Science (CSECS), International Conference on

作者： Jialu Xu Xiaonan Liu Pengchao Li Jintao Wang Haibing Guo School of Information Science and Engineering Shenyang University of Technology Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Tianjin SIASUN Robot & Automation Co. LTD. Tianjin China

The requirements of high-end manufacturing cannot be fulfilled by industrial robot absolute positioning accuracy. A study of algorithms for improving absolute positioning accuracy in industrial robots. An improved sparrow search algorithm (ISSA) incorporating a chaotic mapping initialization population, a butterfly global search strategy, a triangle wandering strategy, and a t-distribution perturbation is proposed to identify the kinematic parameters of industrial robots. First, a robot kinematics model is established based on modified Denavit-Hartenberg (MD-H) parameters. Secondly, verify the effectiveness of the ISSA algorithm. Finally, the kinematic parameters of four T6A-19 industrial robots were determined and adjusted for validation using the ISSA algorithm. The results of the experiment demonstrate an 85.39% improvement in the accuracy of the mean absolute positional error and an 83.36% improvement in the root mean square accuracy. These results support the effectiveness and practicality of the method used.

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Permanent Magnet Shape Optimization Method for PMSM Air Gap Flux Density Harmonics Reduction

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CES Transactions on Electrical Machines and Systems 2021年第4期5卷 284-290页

作者： Chengsi Liu Yongxiang Xu Jibin Zou Guodong Yu Liang Zhuo School of Electrical Engineering and Automation of HIT Department of Electrical Engineering Harbin Institute of Technology the State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Institute of Technology and National Engineering Research Center for Small and Special Precision Motors Guizhou Aerospace Linquan Motor Co.Ltd

This paper proposed a permanent magnet optimization method to suppress the air gap flux density harmonic of permanent magnet synchronous motor(PMSM).The method corrected the effective air gap length of the motor,calculated the magnetization length of the permanent in the case of parallel magnetization,and took the influence of the permanent magnet relative permeability into *** on these works,for a given sinusoidal air gap flux density waveform,the corresponding structural parameters can be calculated,so as to achieve the optimization of the permanent *** using this method to optimize the shape of the magnet,the fundamental wave of the air gap flux density can be retained to the greatest extent,so as to eliminate harmonics and maintain the output capacity at the same *** feasibility and accuracy of the method have been verified by finite element analysis(FEA)and prototype machine *** method is simple and time-saving,and has a satisfactory accuracy,which provides a reference method for permanent magnet optimization of PMSM.

关键词： Permanent magnet synchronous motor(PMSM) analytical method finite element analysis(FEA) magnet shape optimization.

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Towards Fast Face Image Quality Assessment via Latent Diffusion Model 18th

Towards Fast Face Image Quality Assessment via Latent Diffu...

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18th Chinese Conference on Biometric Recognition, CCBR 2024

作者： Yan, Zheyu Zhao, Weisong Zhu, Xiangyu Gao, Li Zhang, Xiao-Yu Lei, Zhen State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China China Mobile Financial Technology Co. Ltd. Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences Hong Kong Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789819610679

Face recognition technology has gradually come into wide application in real life. However, in real-life unconstrained scenarios, low-quality images could be matched to unpredictable individuals, thereby affecting the stability of recognition and even causing security problems. Conducting quality assessment on face images before facial recognition can help alleviate these problems by rejecting low-quality samples. In this paper, we propose a Fast Diffusion-model-based Face Image Quality Assessment method (FDif-FIQA). It uses a diffusion model to perturb face images and measures image quality based on the similarity of features before and after the perturbation. The denoising process is transferred from the pixel space to the latent space, thereby reducing the computational cost. We evaluated the performance of this method with multiple mainstream face recognition models on various public datasets. Compared to state-of-the-art methods, our approach demonstrates highly competitive performance and significant improvements in computational efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Face recognition

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IVR-SSM: Industrial Vehicular Robot Safe & Smart Move Using Wheel-Encoder and Inertial-RGB-Depth Measurements

IVR-SSM: Industrial Vehicular Robot Safe & Smart Move Using ...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Yuanhao Liu Wei Liang Chu Wang Xin Zhang Huanbing Gao Yinlong Zhang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences School of Information and Electrical Engineering Shandong Jianzhu University Shandong Key Laboratory of Intelligent Buildings Technology Jinan China

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

Safe & smart move (SSM) aims to help industrial vehicular robot (IVR), such as warehousing robots, running safely and smartly by detecting the obstacles in front and maintaining a safe distance & attitude. However, the traditional SSM methods suffer the drawbacks of limited ranges, inaccurate regression of safety distance & orientation between the robot and the forward unexpected obstacles, and the inappropriate IVR control strategies. To solve these issues, this paper designs an innovative real-time safety-aware framework using the complementary Wheel-Encoder and Inertial-RGB-Depth measurements to ensure the IVR running safely, reasonably and reliably. To estimate the robot running states, we take advantages of the complementary wheel encoder, monocular RGB images and inertial measurements to obtain the robot positions, orientations, angular and linear velocities in a tightly-coupled manner. To improve the safety relative distance & attitude estimation accuracy, we exploit the RGB and depth measurements in a task-oriented fashion. The forward obstacles with the specific contours are detected using the Mask-RCNN model, followed by the Gaussian Mixture Model to obtain the forward obstacle depth. Eventually, an IVR control strategy is designed to maintain the robot safety distance and orientation, and to keep the minimum damage to the robot mechanical system. The presented method has been evaluated on the developed industrial vehicular robot safety perception platform. The experimental results prove the competitiveness against the state-of-the-art methods.

关键词： Service robots Warehousing Robot vision systems Wheels Reliability engineering Safety Mobile robots Mechanical systems Velocity measurement Gaussian mixture model

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