IEEE transactions on medical robotics and bionics最新文献

{"title":"The LINGCAI-II System: A Sampling Robotic System for Autonomous Oropharyngeal Swab Sampling","authors":"Zhenxing Wang;Shaoqiang Li;Xiao He;Ruchong Chen;Lianqing Liu;Shiyue Li;Hao Liu","doi":"10.1109/TMRB.2024.3377360","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3377360","url":null,"abstract":"The fight against infectious diseases is a permanent theme in the history of humans, especially the pandemic of COVID-19 made a severe impact on the world. The sampling robot which can instead of medical staff in the oropharyngeal swab(OP-swab) sampling is a new form of medical robot that emerged during the pandemic. Robot with continuous automatic sampling capability, which can maximize the value of robots. In this paper, we presented the LINGCAI-II robot, which is the upgrade of the LINGCAI-I robot and can realize the automatic OP-swab sampling in clinical application. Based on the intraoral image and contact force, we proposed an automatic sampling method for robots which includes a three-level visual identification algorithm, trajectory planner, force position hybrid controller, and quality evaluator. By cooperating with other function stations inside the robot, the LINGCAI-II robot can complete the whole process of the sample without manual assistance. The volunteer trial results show that the robot sampling can get more cells in the swab tip than the manual sample. We set up a robot sampling workstation and carried out the clinical trial for 116 COVID-19 patients. Our clinical trials achieved 96 COVID-19 patients diagnosed by robot sampling. This is the first time that the sampling robot achieved application for confirmed patients automatically. The results demonstrated the feasibility of automatic robot sampling in infectious diseases.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of Forearm Postures on Hand-Wrist Gesture Recognition With Forearm Deformation Measurements","authors":"Sung-Gwi Cho;Muhammad Akmal Bin Mohammed Zaffir;Masahiro Yoshikawa;Jun Takamatsu;Takahiro Wada","doi":"10.1109/TMRB.2024.3377364","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3377364","url":null,"abstract":"In hand-wrist gesture recognition based on biosignal, the negative influence of forearm posture variation on recognition accuracy is a common problem. Although the elbow/forearm-rotation angle influence has been investigated in several previous studies, the combined influence of these angles is still unclear. Therefore, we investigated the influence of forearm postures (both elbow and forearm rotation angles) by comparing the accuracies under various data configurations in which the posture combinations used for training the recognition model were different. We collected forearm deformation as biosignal for seven hand-wrist gestures under nine different forearm postures (combinations of three elbow and forearm rotation angles). The accuracy comparison results showed that the forearm rotation angle strongly affected recognition compared with the elbow angle, and the complex combination of elbow and forearm rotation angles had a stronger influence. The results of this study suggest that data collection can be made efficient by considering variations in the forearm postures. If time is available for data collection, it is effective to focus on the interpolation of forearm deformation to the untrained forearm postures based on those of the trained posture. If the time for data collection is limited, it is preferable to focus on variations in forearm rotation angle.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a 7-DoF Haptic Operator Interface Based on Redundantly Actuated Parallel Mechanism","authors":"Jichen Li;Ziyan Huang;Chengzhi Hu;Zhiqiang Zhang;Chaoyang Shi","doi":"10.1109/TMRB.2024.3377376","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3377376","url":null,"abstract":"This paper proposes a novel 7-DoF operator interface based on a redundantly actuated parallel architecture of 2(RRRS)-RRRSP. This design effectively avoids the workspace-internal singularities, thereby addressing the limitations associated with the orientational workspace of traditional parallel operator interfaces. Furthermore, the redundantly actuated mechanism enables 3-DoF full actuation of each branch chain, and the motors are specially positioned near the base, significantly reducing the operating inertia without the need for gravity compensation. This arrangement contributes to a reduction in operator fatigue during prolonged operation. A hybrid tendon-linkage transmission is utilized in the operator interface to enhance its positioning accuracy. A prototype of the operator interface has been developed, and its kinematics along with the Jacobian have been derived. Optimization of structural parameters has been executed to enhance operational dexterity and relative workspace. Static force analysis has been conducted, and a strategy for static force output has been implemented to effectively decouple the interference between the clamping feedback force and the six-dimensional spatial feedback force. Experimental investigations on the translational and orientational workspace are carried out. The results demonstrate an expansive translational workspace measuring 315 mm (X), 248.5 mm, and 133.8 mm (Z), along with a wide range of orientation angles [−108°, 98°] \u0000<inline-formula> <tex-math>$(alpha)$ </tex-math></inline-formula>\u0000, [−134°, 134°] \u0000<inline-formula> <tex-math>$(beta)$ </tex-math></inline-formula>\u0000 and [−115°, 115°] \u0000<inline-formula> <tex-math>$(gamma)$ </tex-math></inline-formula>\u0000. Trajectory tracking experiments have been performed and yielded an average error value of 1.021mm. The accuracy of the feedback force output has been studied, with average errors in output force recorded as 0.084 N (X), 0.124 N (Y), and 0.237 N (Z). Investigations into decoupling capability have been carried out, with average output errors of the clamping force at 5 N and 7 N operating forces in X and Y directions recorded as 0.095 N and 0.081 N, respectively. The experimental results demonstrate its potential for integration into RAMIS systems to align with diverse configurations of slave manipulators.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Robotic Healthcare Device for Treating Chronic Venous Insufficiency in People Who Sit for Prolonged Periods","authors":"Hyeoncheol Kim;Donghyun Kwon;Jangwon Son;Jungsu Choi","doi":"10.1109/TMRB.2024.3373909","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3373909","url":null,"abstract":"Deterioration of the lower limb venous circulation can cause several health problems (e.g., varicose veins, deep vein thrombosis, and cardiac arrhythmia). However, it is not easy to avoid owing to a sedentary life, which is one of the characteristics of modern people. Several studies have focused on improving lower limb blood circulation, and some have used robotic devices. These robots, however, not only the lead to poor blood circulation, but also are too bulky and heavy to use in daily life. In this study, a new type of lower limb venous circulation robot called Healthy-CAL is proposed. By applying the semi auto locking linkage mechanism, the size of Healthy-CAL was reduced while the operating range of the robot was maximized. In addition, a foot mapping algorithm was applied to Healthy-CAL, which autonomously recognizes the user’s ankle joint range of motion and allows users to perform maximized ankle exercises regardless of the sitting position. An experiment was conducted with eight participants to demonstrate the effectiveness of the proposed foot-mapping algorithm. We also used Doppler ultrasound in five participants to confirm the improvement in venous circulation with Healthy-CAL.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Transactions on Medical Robotics and Bionics Society Information","authors":"","doi":"10.1109/TMRB.2024.3391673","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3391673","url":null,"abstract":"","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10517715","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Transactions on Medical Robotics and Bionics Publication Information","authors":"","doi":"10.1109/TMRB.2024.3391671","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3391671","url":null,"abstract":"","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10517713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Transactions on Medical Robotics and Bionics Information for Authors","authors":"","doi":"10.1109/TMRB.2024.3391675","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3391675","url":null,"abstract":"","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10517693","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robotic Repositioning of Photoacoustic Tomography for Reproducible Long-Term Monitoring of Peripheral Artery In Vivo","authors":"Yongjian Zhao;Handi Deng;Xianghu Yu;Yisong Zhao;Ao Xu;Yuhan Chen;Cheng Ma;Li Liu","doi":"10.1109/TMRB.2024.3371542","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3371542","url":null,"abstract":"This paper presents a robotic arm assisted photoacoustic tomography imager that employs a direct visual servoing-enabled repositioning strategy designed for reproducible surveillance of peripheral arterial disease (PAD) progression. The system ensures precise repositioning of the cross-sectional location of the vessel of interest, allowing consistent measurements to track PAD progression and response to treatment. This strategy overcomes the difficulty of obtaining cross-sectional images of the same vessel at different monitoring intervals due to operator variability. In addition, the acquisition of high-resolution, high-contrast vessel images helps to clearly delineate long-term changes in the vasculature. To evaluate the effectiveness of the proposed experimental configurations and algorithms, we performed two sets of vascular phantom experiments and one set of servo-imaging experiments on human lower extremity vessels. The experimental results show 100% similarity for all three sets of grid segmentation comparisons, while the pixel-wise comparison similarity is 99.3% for the first set, 97.4% for the second set, and 98.9% for the in vivo experimental set. These results are important for monitoring the progression of PAD and predicting the risk of cardiovascular disease.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional Resistance Training During Walking: Do Biomechanical and Neural Effects Differ Based on Targeted Joints?","authors":"Edward P. Washabaugh;Chandramouli Krishnan","doi":"10.1109/TMRB.2024.3369894","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3369894","url":null,"abstract":"Devices for functional resistance training (FRT) during walking are often configured to resist the knee or both the hip and knee joints. Adding resistance to the hip in addition to the knee should alter the effects of training; however, these configurations have not been directly compared. We examined how FRT during walking differs during the knee or hip and knee conditions. Fourteen non-disabled individuals received FRT during treadmill walking with a device configured to provide a viscous resistance to the knee or the hip and knee during separate visits. Between these configurations, we compared gait kinetics, muscle activation, kinematic aftereffects, peripheral fatigue, and corticospinal excitability. Adding resistance to the hip increased hip flexion moment and concentric power during the swing phase. However, this did not result in significant differences in muscle activation, aftereffects, peripheral fatigue, or corticospinal excitability between the configurations. Instead, both configurations produced similar changes in these variables. These results indicate that, aside from kinetics, walking with resistance at the hip and knee was not different from resisting the knee in the acute setting. However, further research is needed to determine if long-term training with resistance at the hip induces differential effects than resisting the knee alone.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Lateral Branched Network for Tool Segmentation During Robot-Assisted Endovascular Interventions","authors":"Olatunji Mumini Omisore;Toluwanimi Oluwadara Akinyemi;Wenke Duan;Wenjing Du;Lei Wang","doi":"10.1109/TMRB.2024.3369765","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3369765","url":null,"abstract":"Robot-assisted endovascular intervention has emerged for improving the outcomes of cardiovascular interventions. However, the current segmentation methods are affected with low and varied contrast values of endovascular tools in the angiogram, and background noise, both of which affect segmentation performance. Thus, surgical scene analytics are characterized with slow tool visualization and response during endovascular navigation. In this study, a multi-lateral branched network (MLB-Net) is proposed for pixel-level segmentation of guidewire in angiograms recorded during robot-assisted cardiovascular catheterization. The network has an encoder with lateral separable convolutions and depth-wise attention, and decoder with improved loss function. Feature maps extracted during end-to-end fully supervised training were optimized for guidewire segmentation. The MLB-Net was trained and validated with multiple angiogram sequences obtained during series of robot-assisted catheterization in rabbit model. Validation studies show a robust performance, characterized with mean IoU of 84.89% and area under curve of 90.64%. In addition, the model offered fast (15.28 frame/second) and reliable segmentation performance in new angiograms obtained during additional trials carried out in pig and human phantom models. Furthermore, we evaluated the MLB-Net by comparing it with existing state-of-the-art networks. Based on our rabbit dataset, the MLB-Net offers better segmentation experience over DeepLabV3+, SegNet, and U-Net which are commonly used for medical image segmentation. Also, MLB-Net generalized well under incremental training. This study contributes a new model for fast tool segmentation, tracking and visualization and during endovascular catheterization.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140820379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}