{"title":"ProACT:智能假肢臂增强现实试验台","authors":"Shivani Guptasarma;Monroe D. Kennedy","doi":"10.1109/TNSRE.2024.3521923","DOIUrl":null,"url":null,"abstract":"Upper-limb amputees face tremendous difficulty in operating dexterous powered prostheses. Previous work has shown that aspects of prosthetic hand, wrist, or elbow control can be improved through “intelligent” control, by combining movement-based or gaze-based intent estimation with low-level robotic autonomy. However, no such solutions exist for whole-arm control. Moreover, hardware platforms for advanced prosthetic control are expensive, and existing simulation platforms are not well-designed for integration with robotics software frameworks. We present the Prosthetic Arm Control Testbed (ProACT), a platform for evaluating intelligent control methods for prosthetic arms in an immersive (Augmented Reality) simulation setting. We demonstrate the use of ProACT through preliminary studies, with non-amputee participants performing an adapted Box-and-Blocks task with and without intent estimation. We further discuss how our observations may inform the design of prosthesis control methods, as well as the design of future studies using the platform. To the best of our knowledge, this constitutes the first study of semi-autonomous control for complex whole-arm prostheses, the first study including sequential task modeling in the context of wearable prosthetic arms, and the first testbed of its kind. Towards the goal of supporting future research in intelligent prosthetics, the system is built upon existing open-source frameworks for robotics, and is available at <uri>https://arm.stanford.edu/proact</uri>.","PeriodicalId":13419,"journal":{"name":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","volume":"33 ","pages":"354-365"},"PeriodicalIF":4.8000,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817583","citationCount":"0","resultStr":"{\"title\":\"ProACT: An Augmented Reality Testbed for Intelligent Prosthetic Arms\",\"authors\":\"Shivani Guptasarma;Monroe D. Kennedy\",\"doi\":\"10.1109/TNSRE.2024.3521923\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Upper-limb amputees face tremendous difficulty in operating dexterous powered prostheses. Previous work has shown that aspects of prosthetic hand, wrist, or elbow control can be improved through “intelligent” control, by combining movement-based or gaze-based intent estimation with low-level robotic autonomy. However, no such solutions exist for whole-arm control. Moreover, hardware platforms for advanced prosthetic control are expensive, and existing simulation platforms are not well-designed for integration with robotics software frameworks. We present the Prosthetic Arm Control Testbed (ProACT), a platform for evaluating intelligent control methods for prosthetic arms in an immersive (Augmented Reality) simulation setting. We demonstrate the use of ProACT through preliminary studies, with non-amputee participants performing an adapted Box-and-Blocks task with and without intent estimation. We further discuss how our observations may inform the design of prosthesis control methods, as well as the design of future studies using the platform. To the best of our knowledge, this constitutes the first study of semi-autonomous control for complex whole-arm prostheses, the first study including sequential task modeling in the context of wearable prosthetic arms, and the first testbed of its kind. Towards the goal of supporting future research in intelligent prosthetics, the system is built upon existing open-source frameworks for robotics, and is available at <uri>https://arm.stanford.edu/proact</uri>.\",\"PeriodicalId\":13419,\"journal\":{\"name\":\"IEEE Transactions on Neural Systems and Rehabilitation Engineering\",\"volume\":\"33 \",\"pages\":\"354-365\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-12-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817583\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Neural Systems and Rehabilitation Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10817583/\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10817583/","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
ProACT: An Augmented Reality Testbed for Intelligent Prosthetic Arms
Upper-limb amputees face tremendous difficulty in operating dexterous powered prostheses. Previous work has shown that aspects of prosthetic hand, wrist, or elbow control can be improved through “intelligent” control, by combining movement-based or gaze-based intent estimation with low-level robotic autonomy. However, no such solutions exist for whole-arm control. Moreover, hardware platforms for advanced prosthetic control are expensive, and existing simulation platforms are not well-designed for integration with robotics software frameworks. We present the Prosthetic Arm Control Testbed (ProACT), a platform for evaluating intelligent control methods for prosthetic arms in an immersive (Augmented Reality) simulation setting. We demonstrate the use of ProACT through preliminary studies, with non-amputee participants performing an adapted Box-and-Blocks task with and without intent estimation. We further discuss how our observations may inform the design of prosthesis control methods, as well as the design of future studies using the platform. To the best of our knowledge, this constitutes the first study of semi-autonomous control for complex whole-arm prostheses, the first study including sequential task modeling in the context of wearable prosthetic arms, and the first testbed of its kind. Towards the goal of supporting future research in intelligent prosthetics, the system is built upon existing open-source frameworks for robotics, and is available at https://arm.stanford.edu/proact.
期刊介绍:
Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.