IEEE Transactions on Human-Machine Systems最新文献

{"title":"Machine Learning for Human–Machine Systems With Advanced Persistent Threats","authors":"Long Chen;Wei Zhang;Yanqing Song;Jianguo Chen","doi":"10.1109/THMS.2024.3439625","DOIUrl":"https://doi.org/10.1109/THMS.2024.3439625","url":null,"abstract":"This article conducts a thorough exploration of the implications of machine learning (ML) in conjunction with human–machine systems within the military domain. It scrutinizes the strategic development efforts of ML by pertinent institutions, particularly in the context of military applications and the domain of advanced persistent threats. Prominent nations have delineated a technical trajectory for the integration of ML into their military frameworks. To bolster the structure and efficacy of their various military branches and units, there has been a concentrated deployment of numerous ML research endeavors. These initiatives encompass the study of sophisticated ML algorithms and the acceleration of artificial intelligence technology adaptation for intelligence processing, autonomous platforms, command and control infrastructures, and weapons systems. Forces across the globe are actively embedding ML technologies into a range of platforms-terrestrial, naval, aerial, space-faring, and cybernetic. This integration spans weaponry, networks, cognitive operations, and additional systems. Furthermore, this article reviews the incorporation within the sphere of military human–machine interaction in the Russia–Ukraine conflict. In this war, cyber human–machine interaction has become a pivotal arena of contention between Russia and Ukraine, with key levers that influence the conflict's course. In addition, the article examines the adoption of ML in prospective military functions such as, operations, intelligence gathering, networking, logistics, identification protocols, healthcare, data analysis trends, and other critical areas marked by current developments and trajectories. It also proffers a series of recommendations for the future integration of ML to inform strategic direction and research.","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 6","pages":"753-761"},"PeriodicalIF":3.5,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Bioinspired Virtual Reality Toolkit for Robot-Assisted Medical Application: BioVRbot","authors":"Hang Su;Francesco Jamal Sheiban;Wen Qi;Salih Ertug Ovur;Samer Alfayad","doi":"10.1109/THMS.2024.3462416","DOIUrl":"https://doi.org/10.1109/THMS.2024.3462416","url":null,"abstract":"The increasingly pervasive usage of robotic surgery not only calls for advances in clinical application but also implies high availability for preliminary medical education using virtual reality. Virtual reality is currently upgrading medical education by presenting complicated medical information in an immersive and interactive way. A system that allows multiple users to observe and operate via simulated surgical platforms using wearable devices has become an efficient solution for teaching where a real surgical platform is not available. This article developed a bioinspired virtual reality toolkit (BioVRbot) for education and training in robot-assisted minimally invasive surgery. It allows multiple users to manipulate the robots working on cooperative virtual surgery using bioinspired control. The virtual reality scenario is implemented using unity and can be observed with independent virtual reality headsets. A MATLAB server is designed to manage robot motion planning of incremental teleoperation compliance with the remote center of motion constraints. Wearable sensorized gloves are adopted for continuous control of the tooltip and the gripper. Finally, the practical use of the developed surgical virtual system is demonstrated with cooperative operation tasks. It could be further spread into the classroom for preliminary education of robot-assisted surgery for early-stage medical students.","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 6","pages":"688-697"},"PeriodicalIF":3.5,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Speech-Driven Gesture Generation Using Transformer-Based Denoising Diffusion Probabilistic Models","authors":"Bowen Wu;Chaoran Liu;Carlos Toshinori Ishi;Hiroshi Ishiguro","doi":"10.1109/THMS.2024.3456085","DOIUrl":"https://doi.org/10.1109/THMS.2024.3456085","url":null,"abstract":"While it is crucial for human-like avatars to perform co-speech gestures, existing approaches struggle to generate natural and realistic movements. In the present study, a novel transformer-based denoising diffusion model is proposed to generate co-speech gestures. Moreover, we introduce a practical sampling trick for diffusion models to maintain the continuity between the generated motion segments while improving the within-segment motion likelihood and naturalness. Our model can be used for online generation since it generates gestures for a short segment of speech, e.g., 2 s. We evaluate our model on two large-scale speech-gesture datasets with finger movements using objective measurements and a user study, showing that our model outperforms all other baselines. Our user study is based on the Metahuman platform in the Unreal Engine, a popular tool for creating human-like avatars and motions.","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 6","pages":"733-742"},"PeriodicalIF":3.5,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10712170","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing Surgeon–Robot Cooperative Performance in Robot-Assisted Intravascular Catheterization","authors":"Wenjing Du;Guanlin Yi;Olatunji Mumini Omisore;Wenke Duan;Toluwanimi Oluwadra Akinyemi;Xingyu Chen;Jiang Liu;Boon-Giin Lee;Lei Wang","doi":"10.1109/THMS.2024.3452975","DOIUrl":"https://doi.org/10.1109/THMS.2024.3452975","url":null,"abstract":"Robot-assisted catheterization offers a promising technique for cardiovascular interventions, addressing the limitations of manual interventional surgery, where precise tool manipulation is critical. In remote-control robotic systems, the lack of force feedback and imprecise navigation challenge cooperation between the surgeon and robot. This study proposes a manipulation-based evaluation framework to assess the cooperative performance between different operators and robot using kinesthetic, kinematic, and haptic data from multi-sensor technologies. The proposed evaluation framework achieves a recognition accuracy of 99.99% in assessing the cooperation between operator and robot. Additionally, the study investigates the impact of delay factors, considering no delay, constant delay, and variable delay, on cooperation characteristics. The findings suggest that variable delay contributes to improved cooperation performance between operator and robot in a primary-secondary isomorphic robotic system, compared to a constant delay factor. Furthermore, operators with experience in manual percutaneous coronary interventions exhibit significantly better cooperative manipulate on with the robot system than those without such experience, with respective synergy ratios of 89.66%, 90.28%, and 91.12% based on the three aspects of delay consideration. Moreover, the study explores interaction information, including distal force of tools-tissue and contact force of hand-control-ring, to understand how operators with different technical skills adjust their control strategy to prevent damage to the vascular vessel caused by excessive force while ensuring enough tension to navigate complex paths. The findings highlight the potential of variable delay to enhance cooperative control strategies in robotic catheterization systems, providing a basis for optimizing surgeon-robot collaboration in cardiovascular interventions.","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 6","pages":"698-710"},"PeriodicalIF":3.5,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705684","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Modified Dynamic Movement Primitive Algorithm for Adaptive Gait Control of a Lower Limb Exoskeleton","authors":"Lingzhou Yu;Shaoping Bai","doi":"10.1109/THMS.2024.3458905","DOIUrl":"https://doi.org/10.1109/THMS.2024.3458905","url":null,"abstract":"A major challenge in the lower limb exoskeleton for walking assistance is the adaptive gait control. In this article, a modified dynamic movement primitive (DMP) (MDMP) control is proposed to achieve gait adjustment with different assistance levels. This is achieved by inclusion of interaction forces in the formulation of DMP, which enables learning from physical human–robot interaction. A threshold force is introduced accounting for different levels of walking assistance from the exoskeleton. The MDMP is, thus, capable of generating adjustable gait and reshaping trajectories with data from the interaction force sensors. The experiments on five subjects show that the average differences between the human body and the exoskeleton are 4.13° and 1.92° on the hip and knee, respectively, with average interaction forces of 42.54 N and 26.36 N exerted on the subjects' thigh and shank. The results demonstrated that the MDMP method can effectively provide adjustable gait for walking assistance.","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 6","pages":"778-787"},"PeriodicalIF":3.5,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Present a World of Opportunity","authors":"","doi":"10.1109/THMS.2024.3458771","DOIUrl":"https://doi.org/10.1109/THMS.2024.3458771","url":null,"abstract":"","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 5","pages":"631-631"},"PeriodicalIF":3.5,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684407","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142246401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Systems, Man, and Cybernetics Society Information","authors":"","doi":"10.1109/THMS.2024.3458751","DOIUrl":"https://doi.org/10.1109/THMS.2024.3458751","url":null,"abstract":"","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 5","pages":"C2-C2"},"PeriodicalIF":3.5,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684410","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142246457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Systems, Man, and Cybernetics Society Information","authors":"","doi":"10.1109/THMS.2024.3458753","DOIUrl":"https://doi.org/10.1109/THMS.2024.3458753","url":null,"abstract":"","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 5","pages":"C3-C3"},"PeriodicalIF":3.5,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684376","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142246522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Connect. Support. Inspire.","authors":"","doi":"10.1109/THMS.2024.3458773","DOIUrl":"https://doi.org/10.1109/THMS.2024.3458773","url":null,"abstract":"","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 5","pages":"632-632"},"PeriodicalIF":3.5,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684413","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142246558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TechRxiv: Share Your Preprint Research with the World!","authors":"","doi":"10.1109/THMS.2024.3458769","DOIUrl":"https://doi.org/10.1109/THMS.2024.3458769","url":null,"abstract":"","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 5","pages":"630-630"},"PeriodicalIF":3.5,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684416","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142246521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}