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Woven fabric triboelectric nanogenerators for human-computer interaction and physical health monitoring

Nano Research 2024年第6期17卷 5540-5548页

作者： Yu Miao Mengjuan Zhou Jia Yi Yanyan Wang Guangjin Tian Hongxia Zhang Wenlong Huang Wenhao Wang Ronghui Wu Liyun Ma College of Textile and Clothing Xinjiang UniversityUrumqi 830046China College of Textiles Donghua UniversityShanghai 201620China College of Physics Xiamen UniversityXiamen 201620China Department of Bioengineering Imperial College LondonLondon SW72AZUK

Triboelectric nanogenerator(TENG)converts mechanical energy into valuable electrical energy,offering a solution for future energy needs.As an indispensable part of TENG,textile TENG(T-TENG)has incredible advantages in harvesting biomechanical energy and physiological signal monitoring.However,the application of T-TENG is restricted,partly because the fabric structure parameter and structure on T-TENG performance have not been fully exploited.This study comprehensively investigates the effect of weaving structure on fabric TENGs(F-TENGs)for direct-weaving yarn TENGs and post-coating fabric TENGs.For direct-weaving F-TENGs,a single-yarn TENG(Y-TENG)with a core-sheath structure is fabricated using conductive yarn as the core layer yarn and polytetrafluoroethylene(PTFE)filaments as the sheath yarn.Twelve fabrics with five different sets of parameters were designed and investigated.For post-coating F-TENGs,fabrics with weaving structures of plain,twill,satin,and reinforced twill were fabricated and coated with conductive silver paint.Overall,the twill F-TENGs have the best electrical outputs,followed by the satin F-TENGs and plain weave F-TENGs.Besides,the increase of the Y-TENG gap spacing was demonstrated to improve the electrical output performance.Moreover,T-TENGs are demonstrated for human-computer interaction and self-powered real-time monitoring.This systematic work provides guidance for the future T-TENG’s design.

关键词： single-yarn triboelectric nanogenerators woven fabric triboelectric nanogenerators fabric weaving structures and parameters human-computer interaction physical health monitoring

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Natural human–computer interaction control of multi operators in collaborative virtual maintenance based on optical human motion capture system

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International Journal of Modeling, Simulation, and Scientific Computing 2016年第2期7卷 48-62页

作者： Xiangyang Li Zhili Zhang Feng Liang Qinhe Gao Lilong Tan Xi’an Research Institute of Hi–Tech Xi’an People’s Republic of China

Aiming at the human–computer interaction control(HCIC)requirements of multi operators in collaborative virtual maintenance(CVM),real-time motion capture and simulation drive of multi operators with optical human motion capture system(HMCS)is proposed.The detailed realization process of real-time motion capture and data drive for virtual operators in CVM environment is presented to actualize the natural and online interactive operations.In order to ensure the cooperative and orderly interactions of virtual operators with the input operations of actual operators,collaborative HCIC model is established according to specific planning,allocating and decision-making of different maintenance tasks as well as the human–computer interaction features and collaborative maintenance operation features among multi maintenance trainees in CVM process.Finally,results of the experimental implementation validate the effectiveness and practicability of proposed methods,models,strategies and mechanisms.

关键词： human-computer interaction collaborative virtual maintenance virtual reality human motion capture system concurrent conflict control mechanism.

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Dynamic constraint and objective generation approach for real-time train rescheduling model under human-computer interaction

High-Speed Railway

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High-Speed Railway 2023年第4期1卷 248-257页

作者： Kai Liu Jianrui Miao Zhengwen Liao Xiaojie Luan Lingyun Meng School of Traffic and Transportation Beijing Jiaotong UniversityBeijing 100044China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China

Real-time train rescheduling plays a vital role in railway transportation as it is crucial for maintaining punctuality and reliability in rail operations.In this paper,we propose a rescheduling model that incorporates constraints and objectives generated through human-computer interaction.This approach ensures that the model is aligned with practical requirements and daily operational tasks while facilitating iterative train rescheduling.The dispatcher’s empirical knowledge is integrated into the train rescheduling process using a human-computer interaction framework.We introduce six interfaces to dynamically construct constraints and objectives that capture human intentions.By summarizing rescheduling rules,we devise a rule-based conﬂict detection-resolution heuristic algorithm to effectively solve the formulated model.A series of numerical experiments are presented,demonstrating strong performance across the entire system.Furthermore,theﬂexibility of rescheduling is enhanced through secondary analysis-driven solutions derived from the outcomes of humancomputer interactions in the previous step.This proposed interaction method complements existing literature on rescheduling methods involving human-computer interactions.It serves as a tool to aid dispatchers in identifying more feasible solutions in accordance with their empirical rescheduling strategies.

关键词： Real-time train rescheduling human-computer interaction Rule-based heuristic algorithm Secondary rescheduling

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Vision-Based Hand Gesture Recognition for human-computer interaction——A Survey

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Wuhan University Journal of Natural Sciences 2020年第2期25卷 169-184页

作者： GAO Yongqiang LU Xiong SUN Junbin TAO Xianglin HUANG Xiaomei YAN Yuxing LIU Jia College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106JiangsuChina School of Automation Nanjing University of Information Science&TechnologyNanjing 210044JiangsuChina

Recently,vision-based gesture recognition(VGR)has become a hot research spot in human-computer interaction(HCI).Unlike other gesture recognition methods with data gloves or other wearable sensors,vision-based gesture recognition could lead to more natural and intuitive HCI interactions.This paper reviews the state-of-the-art vision-based gestures recognition methods,from different stages of gesture recognition process,i.e.,(1)image acquisition and pre-processing,(2)gesture segmentation,(3)gesture tracking,(4)feature extraction,and(5)gesture classification.This paper also analyzes the advantages and disadvantages of these various methods in detail.Finally,the challenges of vision-based gesture recognition in haptic rendering and future research directions are discussed.

关键词： vision-based gesture recognition human-computer interaction state-of-the-art feature extraction

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Virtual Keyboard:A Real-Time Hand Gesture Recognition-Based Character Input System Using LSTM and Mediapipe Holistic

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computer Systems Science & Engineering 2024年第2期48卷 555-570页

作者： Bijon Mallik Md Abdur Rahim Abu Saleh Musa Miah Keun Soo Yun Jungpil Shin Department of computer Science and Engineering Pabna University of Science and TechnologyPabna6600Bangladesh School of computer Science and Engineering The University of AizuAizuwakamatsuFukushima965-8580Japan School of computer and Information Technology Ulsan CollegeDong-guUlsan44610South Korea

In the digital age,non-touch communication technologies are reshaping human-device interactions and raising security concerns.A major challenge in current technology is the misinterpretation of gestures by sensors and cameras,often caused by environmental factors.This issue has spurred the need for advanced data processing methods to achieve more accurate gesture recognition and predictions.Our study presents a novel virtual keyboard allowing character input via distinct hand gestures,focusing on two key aspects:hand gesture recognition and character input mechanisms.We developed a novel model with LSTM and fully connected layers for enhanced sequential data processing and hand gesture recognition.We also integrated CNN,max-pooling,and dropout layers for improved spatial feature extraction.This model architecture processes both temporal and spatial aspects of hand gestures,using LSTM to extract complex patterns from frame sequences for a comprehensive understanding of input data.Our unique dataset,essential for training the model,includes 1,662 landmarks from dynamic hand gestures,33 postures,and 468 face landmarks,all captured in real-time using advanced pose estimation.The model demonstrated high accuracy,achieving 98.52%in hand gesture recognition and over 97%in character input across different scenarios.Its excellent performance in real-time testing underlines its practicality and effectiveness,marking a significant advancement in enhancing human-device interactions in the digital age.

关键词： Hand gesture recognition M.P.holistic open CV virtual keyboard LSTM human-computer interaction

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Reform of human-computer interaction Course based on Mobile Application interaction Design

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计算机教育 2020年第12期 122-125页

作者： Siyang Lu Xiang Wei School of computer and Information Technology Beijing Jiaotong UniversityHaidianBeijing100044China School of Software Engineering Beijing Jiaotong UniversityHaidianBeijing100044China

With the popularity of new intelligent mobile devices in people’s lives,the development of mobile applications has paid increasing attention to the interactive experience of users.As the content of traditional human-computer interaction(HCI)course and teaching material is out of date,it cannot meet the needs of mobile application interaction design and enterprises for students.Therefore,we need a new generation HCI course based on intelligent mobile devices to study the relationship between users and systems.The HCI course not only teaches students HCI theory and model,but also needs to cultivate students’interaction-oriented design practical ability.This paper proposes a set of HCI teaching material design and teaching methods for improving HCI class quality on mobile application interaction design,so as to make students more suitable for the employment requirements of enterprises.

关键词： human-computer interaction software engineering mobile application interaction design

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Research on the Three-Dimensional human-computer interaction based on the Mobile Internet Terminal

Research on the Three-Dimensional Human-Computer Interaction...

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2011 International Conference on Fuzzy Systems and Neural Computing(FSNC 2011)

作者： Lu Ji xiang Wang Ping Tong Ling Zhang Bei College of Mechanical &Electrical Engineering Northwestern Polytechnical University School of Telecommunication Engineering Xidian University Xian International Studies University College of Mingde Northwestern Polytechnical University

The Three-dimensional（3D）human-computer interaction of the wireless mobile communication is becoming the research highlight in the field of the human-computer interaction.As the terminal products of the Mobile Internet the mobile phones,the tablet PC,and etc directly contact the end users,the modal of the content provided and the comfort level of the users are determined by the human-computer interaction,which also further influence weather the users’satisfaction,therefore the product survival in the market.The new virtual human-computer interaction technology of Mobile Internet Terminal（MIT）is explored and studied based on mentioned above in this paper.

关键词： Mobile Internet human-computer interaction Mobile Internet Terminal（MIT）

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Gesture Recognition Based on Time-of-Flight Sensor and Residual Neural Network

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Journal of computer and Communications 2024年第6期12卷 103-114页

作者： Yuqian Ma Zitong Fang Wen Jiang Chang Su Yuankun Zhang Junyu Wu Zhengjie Wang College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao China

With the advancement of technology and the increase in user demands, gesture recognition played a pivotal role in the field of human-computer interaction. Among various sensing devices, Time-of-Flight (ToF) sensors were widely applied due to their low cost. This paper explored the implementation of a human hand posture recognition system using ToF sensors and residual neural networks. Firstly, this paper reviewed the typical applications of human hand recognition. Secondly, this paper designed a hand gesture recognition system using a ToF sensor VL53L5. Subsequently, data preprocessing was conducted, followed by training the constructed residual neural network. Then, the recognition results were analyzed, indicating that gesture recognition based on the residual neural network achieved an accuracy of 98.5% in a 5-class classification scenario. Finally, the paper discussed existing issues and future research directions.

关键词： Hand Posture Recognition human-computer interaction Deep Learning Gesture Datasets Real-Time Processing

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A Survey of Gesture Recognition Using Frequency Modulated Continuous Wave Radar

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Journal of computer and Communications 2024年第6期12卷 115-134页

作者： Xinran Qiu Junhao Liu Lulu Song Haofei Teng Jiaqi Zhang Zhengjie Wang College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao China

With technology advances and human requirements increasing, human-computer interaction plays an important role in our daily lives. Among these interactions, gesture-based recognition offers a natural and intuitive user experience that does not require physical contact and is becoming increasingly prevalent across various fields. Gesture recognition systems based on Frequency Modulated Continuous Wave (FMCW) millimeter-wave radar are receiving widespread attention due to their ability to operate without wearable sensors, their robustness to environmental factors, and the excellent penetrative ability of radar signals. This paper first reviews the current main gesture recognition applications. Subsequently, we introduce the system of gesture recognition based on FMCW radar and provide a general framework for gesture recognition, including gesture data acquisition, data preprocessing, and classification methods. We then discuss typical applications of gesture recognition systems and summarize the performance of these systems in terms of experimental environment, signal acquisition, signal processing, and classification methods. Specifically, we focus our study on four typical gesture recognition systems, including air-writing recognition, gesture command recognition, sign language recognition, and text input recognition. Finally, this paper addresses the challenges and unresolved problems in FMCW radar-based gesture recognition and provides insights into potential future research directions.

关键词： Millimeter-Wave Radar Gesture Recognition human-computer interaction Feature Extraction

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Data Visualization Analysis Based on Explainable Artificial Intelligence:A Survey

IJLAI Transactions on Science and Engineering

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IJLAI Transactions on Science and Engineering 2024年第2期2卷 13-20页

作者： Shoulin Yin Hang Li Yang Sun Muhammad Ibrar Lin Teng Software College Shenyang Normal UniversityShenyang 110034China

With the rapid development of computer hardware and big data processing technology,the bottleneck of intelligent analysis of massive data has changed from“how to deal with massive data quickly”to“how to mine valuable information quickly and effectively from massive data”.Visualization and visualization analysis based on human visual perception characteristics,combined with data analysis and human-computer interaction and other technologies,use visual charts to deconstruct the knowledge and rules contained in complex data.This technology runs through the whole life cycle of data science,known as the last kilometer in the field of big data intelligence,and has achieved remarkable results in many big data application analysis scenarios.Traditional visualization analysis is extremely dependent on the user’s frequent active participation in the whole life cycle of visualization analysis,including data preparation,data conversion,visualization mapping,visual rendering,user interaction,visual analysis and other stages,which require high professional skills of users and low intelligence of the system.Therefore,the traditional visualization analysis mode and systems have the challenges of high threshold of visualization analysis,high cost of data preparation,high latency of interaction response,and low efficiency of interaction mode.Therefore,this paper introduces the application,challenges in visualization based on explainable AI.

关键词： Big data human-computer interaction Visualization analysis Explainable AI

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