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学者姓名：卢宗兴
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Abstract ：
Due to the current focus of research on ankle rehabilitation robots on structural design, there is still limited research on ankle human-machine interaction technology. In order to enable rehabilitation robots to conduct personalized rehabilitation training based on patients' ankle movement intentions, we propose a new ankle motion recognition method based on plantar pressure. First, we designed a plantar pressure collection system based on array sensors. Then, we collected nine types of ankle joint motion pressure data from five volunteers and conducted algorithm selection, data processing, and algorithm optimization. Finally, we proposed a small sample optimization algorithm based on support vector machine, with an average recognition rate of 93.16%. The recognition method proposed in this paper can be combined with ankle rehabilitation robots to achieve active rehabilitation functions, laying the foundation for the clinical application of active rehabilitation technology.
Keyword ：
acquisition system acquisition system algorithm optimization algorithm optimization data processing data processing motion recognition motion recognition Plantar pressure Plantar pressure
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| GB/T 7714 | Lu, Zongxing , Xu, Zhiwei , Zhao, Dongzhe et al. ANKLE JOINT MOTION RECOGNITION SYSTEM AND ALGORITHM OPTIMIZATION BASED ON PLANTAR PRESSURE [J]. | JOURNAL OF MECHANICS IN MEDICINE AND BIOLOGY , 2024 . |
| MLA | Lu, Zongxing et al. "ANKLE JOINT MOTION RECOGNITION SYSTEM AND ALGORITHM OPTIMIZATION BASED ON PLANTAR PRESSURE" . | JOURNAL OF MECHANICS IN MEDICINE AND BIOLOGY (2024) . |
| APA | Lu, Zongxing , Xu, Zhiwei , Zhao, Dongzhe , Yang, Tianxue . ANKLE JOINT MOTION RECOGNITION SYSTEM AND ALGORITHM OPTIMIZATION BASED ON PLANTAR PRESSURE . | JOURNAL OF MECHANICS IN MEDICINE AND BIOLOGY , 2024 . |
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The gesture recognition (GR) technology as one of the human-machine interfaces can conveniently and effectively express the intention of human and has become the hot research hot spot in recent years. Force level is a key factor while GR for more dexterous and natural prosthetic control. To provide researchers with a systematic and quick overview of the relevant and future developments in GR and force assessment (FA) techniques, this review synthesizes current commonly used sensor interfaces, data processing methods, and methods that have improved recognition performance. The experimental design and related results of GR and FA with various types of sensors are analyzed and compared to understand the scope of application and recognition performance of different sensors. This review summarizes the challenges and future work in the five areas of hardware, use environment, broad applicability, physiological factors, and comfort of use in practical applications. Finally, the conclusion prospects that future research may need to focus on improving model generalization and robustness to environmental, physiological factors, and so on by building large datasets and developing flexible, long-lasting, lightweight, and senseless, high-performance interfaces.
Keyword ：
Feature extraction Feature extraction Force Force Force assessment (FA) Force assessment (FA) Gesture recognition Gesture recognition gesture recognition (GR) gesture recognition (GR) human-machine interaction (HMI) human-machine interaction (HMI) Image segmentation Image segmentation Nails Nails sensors sensors Sensors Sensors signal acquisition signal acquisition Support vector machines Support vector machines
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| GB/T 7714 | Lu Zongxing , He Baizheng , Cai Yingjie et al. Human-Machine Interaction Technology for Simultaneous Gesture Recognition and Force Assessment: A Review [J]. | IEEE SENSORS JOURNAL , 2023 , 23 (22) : 26981-26996 . |
| MLA | Lu Zongxing et al. "Human-Machine Interaction Technology for Simultaneous Gesture Recognition and Force Assessment: A Review" . | IEEE SENSORS JOURNAL 23 . 22 (2023) : 26981-26996 . |
| APA | Lu Zongxing , He Baizheng , Cai Yingjie , Chen Bingxing , Yao Ligang , Huang Haibin et al. Human-Machine Interaction Technology for Simultaneous Gesture Recognition and Force Assessment: A Review . | IEEE SENSORS JOURNAL , 2023 , 23 (22) , 26981-26996 . |
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目的 设计一种2-PSU/RR并联踝关节康复机器人，并对人体肌肉进行生物力学特性分析，研究踝关节康复机器人的康复策略。方法 采用数值离散搜索法获得机器人的实际工作空间，探究结构参数变化对机器人动平台高度的影响。通过人体生物力学仿真软件AnyBody得到肌肉力、肌肉活动度等人体生物力学响应，研究动平台高度变化对肌肉行为的影响。结果 机器人能够满足踝关节跖屈/背屈和内翻/外翻运动需求。适当增大定长杆的初始倾角和减小长度，使得踝关节康复机器人具有较低的整体高度。动平台高度依次递减10 mm,人体参与运动的肌肉力和肌肉活动度都有一定幅度下降。结论 本研究为踝关节康复提供一种新的设计方案，为踝康复机器人运动分析提供理论指导，并通过修改机构参数加快患者脚踝康复。
Keyword ：
人机耦合建模 人机耦合建模 参数优化 参数优化 工作空间 工作空间 并联结构 并联结构 踝关节康复机器人 踝关节康复机器人
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| GB/T 7714 | 苏永生 , 卢宗兴 , 李胤增 et al. 踝关节人机耦合生物力学特性分析 [J]. | 医用生物力学 , 2023 , 38 (02) : 389-395 . |
| MLA | 苏永生 et al. "踝关节人机耦合生物力学特性分析" . | 医用生物力学 38 . 02 (2023) : 389-395 . |
| APA | 苏永生 , 卢宗兴 , 李胤增 , 陈晓辉 , 赵栋哲 . 踝关节人机耦合生物力学特性分析 . | 医用生物力学 , 2023 , 38 (02) , 389-395 . |
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为了研究一个典型的风力机塔筒在风-地震耦合作用下的结构性能。通过有限元软件ABAQUS建立塔筒的精细模型，并对其进行非线性时程分析。其中，风载荷基于IECKaimal谱，根据叶素动量理论(BEM)，由风力机载荷计算软件Ashes输出叶片载荷；且将运行状态分为正常运行与故障运行。同时，为了研究不同周期地震波作用下塔筒的结构响应以及失效形式，将地震运动分为两组，一组为短周期地震，另一组为长周期地震。研究发现在风-地震耦合作用下塑性铰首先出现在风力机塔分段连接处，这与风单独作用时失效位置相同；且在短周期地震作用下一旦形成塑性铰将很快导致塔筒整体倒塌；当地震波峰值加速度(PGA)相近时，长周期地震对运行中风力机塔的结构性能影响较大。
Keyword ：
倒塌分析 倒塌分析 故障运行 故障运行 非线性时程分析 非线性时程分析 风力机塔筒 风力机塔筒 风-地震耦合 风-地震耦合
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| GB/T 7714 | 钟建华 , 王永涛 , 卢宗兴 et al. 风力机塔筒在风-地震耦合作用下的非线性时程分析 [J]. | 制造业自动化 , 2023 , 45 (04) : 159-164 . |
| MLA | 钟建华 et al. "风力机塔筒在风-地震耦合作用下的非线性时程分析" . | 制造业自动化 45 . 04 (2023) : 159-164 . |
| APA | 钟建华 , 王永涛 , 卢宗兴 , 陈禹荃 , 叶锦华 . 风力机塔筒在风-地震耦合作用下的非线性时程分析 . | 制造业自动化 , 2023 , 45 (04) , 159-164 . |
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In this paper, we propose a pneumatic double-joint soft actuator based on fiber winding and build a dexterous hand with 11 degrees of freedom. Firstly, soft actuator structural design is carried out according to the actuator driving principle and gives the specific manufacturing process. Then, an experimental analysis of the bending performance of a single soft actuator, including bending angle, speed, and force magnitude, is carried out by building a pneumatic control experimental platform. Finally, a series of dexterous robotic hand-grasping experiments is conducted. Different grasping methods are used to catch the objects and measure the objects' change in height, length, and rotation angle during the experiment. The results show that the proposed soft actuator is more consistent with the bending rule of human fingers, and that the gestures of the dexterous hand are more imaginable and flexible when grasping objects. The soft actuator can carry out horizontal and vertical movements, and rotation of the object in the dexterous hand, thus achieving better human-computer interaction.
Keyword ：
bend performance bend performance dexterous robotic hand dexterous robotic hand double-joint soft actuator double-joint soft actuator
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| GB/T 7714 | Chen, Bingxing , Meng, Qiuxu , Wang, Junjie et al. Experimental Study on Double-Joint Soft Actuator and Its Dexterous Hand [J]. | MICROMACHINES , 2023 , 14 (10) . |
| MLA | Chen, Bingxing et al. "Experimental Study on Double-Joint Soft Actuator and Its Dexterous Hand" . | MICROMACHINES 14 . 10 (2023) . |
| APA | Chen, Bingxing , Meng, Qiuxu , Wang, Junjie , Lu, Zongxing , Cai, Yingjie . Experimental Study on Double-Joint Soft Actuator and Its Dexterous Hand . | MICROMACHINES , 2023 , 14 (10) . |
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为了实现脚踝康复运动,设计开发2UPS/RR脚踝康复机器人;通过螺旋理论对并联机构自由度进行计算,使用闭环矢量法求得机构的逆解方程,应用点集搜索法求得机构得工作空间;调整并研究机构杆件空间位置布局对工作空间及面积的影响,结果表明,优化后的机构的工作空间能够满足脚踝康复所需的运动角度.最后以MATLAB及ADAMS软件通过实例验证逆解正确性,并仿真得到机构确定点在空间中运动轨迹.
Keyword ：
工作空间 工作空间 并联机构 并联机构 螺旋理论 螺旋理论 踝关节康复机器人 踝关节康复机器人 闭环矢量法 闭环矢量法
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| GB/T 7714 | 吴广进 , 卢宗兴 , 于潇雁 . 2UPS/RR脚踝康复机构设计与工作空间优化 [J]. | 机械科学与技术 , 2023 , 42 (1) : 83-91 . |
| MLA | 吴广进 et al. "2UPS/RR脚踝康复机构设计与工作空间优化" . | 机械科学与技术 42 . 1 (2023) : 83-91 . |
| APA | 吴广进 , 卢宗兴 , 于潇雁 . 2UPS/RR脚踝康复机构设计与工作空间优化 . | 机械科学与技术 , 2023 , 42 (1) , 83-91 . |
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Cabinet wiring is a crucial process in the field of electrical engineering. Traditional wiring methods are labor-intensive, time-consuming, and prone to safety hazards. Consequently, robot wiring technology has emerged as a promising solution. This paper investigates how to simulate the cabinet wiring robot using Robot Studio software. The rise of robot wiring technology has brought about novel automation solutions to the field of electrical engineering, improving work efficiency and reducing safety risks. In this automated wiring process, we achieve cabinet automation through the control of upper and lower computers and validate the wiring effectiveness and feasibility of the robot through simulation. During the simulation process, we analyze the relevant parameters of setting reasonable robot offline programming to achieve optimal automation wiring results. This paper aims to provide a novel solution for cabinet wiring work and promote the development and application of automation technology in electrical engineering. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
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| GB/T 7714 | Zhao, C. , Liu, Y. , Lu, Z. . Wiring Simulation of Electric Control Cabinet Based on Industrial Robot [未知]. |
| MLA | Zhao, C. et al. "Wiring Simulation of Electric Control Cabinet Based on Industrial Robot" [未知]. |
| APA | Zhao, C. , Liu, Y. , Lu, Z. . Wiring Simulation of Electric Control Cabinet Based on Industrial Robot [未知]. |
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Abstract ：
As one of the important health indicators of the body, plantar pressure distribution has great reference value in clinical medicine, sports and fitness training, and rehabilitation fields. The purpose of plantar pressure collection is to identify the movement patterns and pressure distribution information of the human lower limbs. This article focuses on introducing the design of plantar pressure detection and motion detection systems from the aspects of array plantar pressure sensors, STM32 acquisition circuits, acquisition programs, and gait segmentation recognition algorithms. During the process of human body state recognition, the collection system sequentially scans 16 plantar pressure sensors and transmits the collected data to the pressure measurement recognition software for real-time graphic display and motion recognition. Wireless communication is carried out using WiFi transmission, and repetitive action segmentation and different pose recognition are achieved using gait segmentation algorithm and SVM algorithm. And a detection system experimental platform was built to recognize 8 daily movements such as sitting, standing, and going up and down stairs, with a recognition rate of 93.65%, laying the experimental foundation for motion parameter analysis and foot rehabilitation evaluation. © 2023 IEEE.
Keyword ：
Gait analysis Gait analysis Motion estimation Motion estimation Pattern recognition Pattern recognition Pressure distribution Pressure distribution Pressure sensors Pressure sensors Sports Sports Sports medicine Sports medicine State estimation State estimation Wearable sensors Wearable sensors Wi-Fi Wi-Fi
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| GB/T 7714 | Xu, Zhiwei , Tian, Chenhao , Zhu, Xiaolin et al. Human Motion State Recognition Method Based on Plantar Pressure Sensing Technology [C] . 2023 : 491-495 . |
| MLA | Xu, Zhiwei et al. "Human Motion State Recognition Method Based on Plantar Pressure Sensing Technology" . (2023) : 491-495 . |
| APA | Xu, Zhiwei , Tian, Chenhao , Zhu, Xiaolin , Lu, Zongxing . Human Motion State Recognition Method Based on Plantar Pressure Sensing Technology . (2023) : 491-495 . |
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Abstract ：
The gesture recognition (GR) technology as one of the human-machine interfaces can conveniently and effectively express the intention of human and has become the hot research hot spot in recent years. Force level is a key factor while GR for more dexterous and natural prosthetic control. To provide researchers with a systematic and quick overview of the relevant and future developments in GR and force assessment (FA) techniques, this review synthesizes current commonly used sensor interfaces, data processing methods, and methods that have improved recognition performance. The experimental design and related results of GR and FA with various types of sensors are analyzed and compared to understand the scope of application and recognition performance of different sensors. This review summarizes the challenges and future work in the five areas of hardware, use environment, broad applicability, physiological factors, and comfort of use in practical applications. Finally, the conclusion prospects that future research may need to focus on improving model generalization and robustness to environmental, physiological factors, and so on by building large datasets and developing flexible, long-lasting, lightweight, and senseless, high-performance interfaces.
Keyword ：
Force assessment (FA) Force assessment (FA) gesture recognition (GR) gesture recognition (GR) human-machine interaction (HMI) human-machine interaction (HMI) sensors sensors signal acquisition signal acquisition
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| GB/T 7714 | Lu, Zongxing , He, Baizheng , Cai, Yingjie et al. Human-Machine Interaction Technology for Simultaneous Gesture Recognition and Force Assessment: A Review [J]. | IEEE SENSORS JOURNAL , 2023 , 23 (22) : 26981-26996 . |
| MLA | Lu, Zongxing et al. "Human-Machine Interaction Technology for Simultaneous Gesture Recognition and Force Assessment: A Review" . | IEEE SENSORS JOURNAL 23 . 22 (2023) : 26981-26996 . |
| APA | Lu, Zongxing , He, Baizheng , Cai, Yingjie , Chen, Bingxing , Yao, Ligang , Huang, Haibin et al. Human-Machine Interaction Technology for Simultaneous Gesture Recognition and Force Assessment: A Review . | IEEE SENSORS JOURNAL , 2023 , 23 (22) , 26981-26996 . |
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Researchers are investigating how to make machines read our body language to make human-machine interaction (HMI) more intelligent and efficient. The lower limbs contain a variety of gestures, and it is also one of the most effective ways to express body information. Therefore, foot gesture recognition (FGR) has become a popular technology for human-machine interface with simple, fast, and accurate features. To give the reader a quick overview of the current state of FGR research, this review takes the sensing methods used in the FGR technology as an entry point, introduces different sensing methods, machine learning algorithms, and applications, and discusses the limitations and future work on FGR systems. The results show that the mainstream sensing methods for FGR are plantar pressure, inertial, visual, surface electromyography (sEMG), and ultrasound (US). Current applications of FGR are simplified control, medical rehabilitation, virtual reality (VR), and smart prosthetics. Research on hybrid sensing methods and deep learning algorithms has gradually increased in recent years. Future research will focus on designing sensor hardware that can respond to environmental changes, using multimodal sensing for interaction, and designing more comfortable and portable FGR systems.
Keyword ：
Ankle joint movement Ankle joint movement foot gesture recognition (FGR) foot gesture recognition (FGR) human-machine interaction (HMI) human-machine interaction (HMI) machine learning machine learning sensors sensors
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| GB/T 7714 | Yue, Lian , Lu Zongxing , Hui, Dong et al. How to Achieve Human-Machine Interaction by Foot Gesture Recognition: A Review [J]. | IEEE SENSORS JOURNAL , 2023 , 23 (15) : 16515-16528 . |
| MLA | Yue, Lian et al. "How to Achieve Human-Machine Interaction by Foot Gesture Recognition: A Review" . | IEEE SENSORS JOURNAL 23 . 15 (2023) : 16515-16528 . |
| APA | Yue, Lian , Lu Zongxing , Hui, Dong , Chao, Jia , Liu Ziqiang , Liu Zhoujie . How to Achieve Human-Machine Interaction by Foot Gesture Recognition: A Review . | IEEE SENSORS JOURNAL , 2023 , 23 (15) , 16515-16528 . |
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