IEEE Transactions on Human-Machine Systems最新文献

{"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}

{"title":"IEEE Transactions on Human-Machine Systems Information for Authors","authors":"","doi":"10.1109/THMS.2024.3458755","DOIUrl":"https://doi.org/10.1109/THMS.2024.3458755","url":null,"abstract":"","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 5","pages":"C4-C4"},"PeriodicalIF":3.5,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142246520","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":"Reconstructing Visual Stimulus Representation From EEG Signals Based on Deep Visual Representation Model","authors":"Hongguang Pan;Zhuoyi Li;Yunpeng Fu;Xuebin Qin;Jianchen Hu","doi":"10.1109/THMS.2024.3407875","DOIUrl":"10.1109/THMS.2024.3407875","url":null,"abstract":"Reconstructing visual stimulus representation is a significant task in neural decoding. Until now, most studies have considered functional magnetic resonance imaging (fMRI) as the signal source. However, fMRI-based image reconstruction methods are challenging to apply widely due to the complexity and high cost of acquisition equipment. Taking into account the advantages of the low cost and easy portability of electroencephalogram (EEG) acquisition equipment, we propose a novel image reconstruction method based on EEG signals in this article. First, to meet the high recognizability of visual stimulus images in a fast-switching manner, we construct a visual stimuli image dataset and obtain the corresponding EEG dataset through EEG signals collection experiment. Second, we introduce the deep visual representation model (DVRM), comprising a primary encoder and a subordinate decoder, to reconstruct visual stimuli representation. The encoder is designed based on residual-in-residual dense blocks to learn the distribution characteristics between EEG signals and visual stimulus images. Meanwhile, the decoder is designed using a deep neural network to reconstruct the visual stimulus representation from the learned deep visual representation. The DVRM can accommodate the deep and multiview visual features of the human natural state, resulting in more precise reconstructed images. Finally, we evaluate the DVRM based on the quality of the generated images using our EEG dataset. The results demonstrate that the DVRM exhibits an excellent performance in learning deep visual representation from EEG signals, generating reconstructed representation of images that are realistic and highly resemble the original images.","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 6","pages":"711-722"},"PeriodicalIF":3.5,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254852","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}