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NCS-FO: Functional and neural mechanisms of integrating multiple artificial somatosensory feedback signals in prosthesis control

NCS-FO: Functional and neural mechanisms of integrating multiple artificial somatosensory feedback signals in prosthesis control
NCS-FO:在假肢控制中集成多个人工体感反馈信号的功能和神经机制
批准号:
2123678
负责人:
Xiaogang Hu
金额:
$30.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-09-01 至 2023-06-30

项目摘要

项目成果

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中文摘要
翻译
截肢后,与肢体相关的运动和感觉功能都丧失了。已经投入了大量的努力来恢复失去的运动功能。相比之下,在恢复感觉功能方面进展较少。虽然早期的工作已经使用感觉替代或神经刺激技术来引起单一类型的人工感觉,但当提供多种感觉刺激时,对人类大脑如何整合不同来源的人工感觉的理解有限。这个项目将有助于理解不同的人工诱发的关节运动感觉的整合原理。通过确定决定多个人工感觉源的集成原理的关键因素,该项目可以为人机交互产生潜在的变革性成果,特别是开发大脑启发的感觉刺激策略,可以实现辅助设备的直观交互。该项目将提供教育机会。不同的项目组成部分将被整合到现有的本科课程。暑期项目包括感官刺激技术将提供给当地学校和社区学院的学生。将针对代表性不足的学生制定与研究成果相关的外联方案。本计画的目的是了解不同人工诱发本体感受回馈的整合原理。研究团队将联合收割机结合心理物理测试、行为建模、大脑信号记录等手段,了解人工感觉信号的整合原理。将使用振动触觉刺激和外周神经刺激诱发关节运动学的本体感受反馈。将研究上肢和下肢,以评估整合原理是否依赖于任务或末端执行器。研究小组将使用贝叶斯整合模型和脑电图(EEG)记录来量化人工反馈的不确定性和直觉相关的注意力偏差如何影响感觉整合。该项目的成果将为开发用于直观人机交互的人工感觉反馈提供理论基础,并将为研究感官感知提供研究平台。该项目由理解神经和认知系统(NCS)的综合策略资助,这是一个由生物学(BIO),计算机和信息科学与工程(CISE),教育和人力资源(EHR),工程(ENG)和社会,行为,该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
After a limb amputation, both motor and sensory functions associated with the limb are lost. Substantial effort has been devoted to restore lost motor functions. In contrast, there has been less advancement in restoring sensory function. Although earlier works have used sensory substitution or nerve stimulation techniques to elicit a single type of artificial sensation, there is limited understanding of how the human brain integrates different sources of artificial sensation, when multiple sensory stimulations are provided. This project will help understand the integration principles of different artificially evoked sensations of joint movements. By identifying key factors that determine the integration principle of multiple sources of artificial sensation, this project can generate potentially transformative outcomes for human-robot interactions, specifically developing brain-inspired sensory stimulation strategies that can enable intuitive interactions of assistive devices. The project will provide educational opportunities. Different project components will be integrated into existing undergraduate courses. Summer projects incorporating the sensory stimulation techniques will be offered to local school and community college students. Outreach programs associated with the research outcomes will be developed targeting underrepresented students. The goal of this project is to understand the integration principles of different artificially evoked proprioceptive feedback. The research team will combine psychophysical testing, behavioral modeling, and brain signal recordings to understand the integration principle of artificial sensory signals. Proprioceptive feedback of the joint kinematics will be evoked using vibrotactile stimulation and peripheral nerve stimulation. Both upper and lower limbs will be investigated to evaluate whether the integration principle is task or end-effector dependent. The research team will use a Bayesian integration model and electroencephalogram (EEG) recordings to quantify how uncertainty and intuitiveness-associated attentional bias of artificial feedback impact sensory integration. The project outcomes will provide a theoretical basis for developing artificial sensory feedback for intuitive human-robot interactions, and will also provide a research platform for studying sensory perception. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NCS), a multidisciplinary program jointly supported by the Directorates for Biology (BIO), Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(2)
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会议论文
DOI: 10.1109/lra.2021.3139147
发表时间: 2022-04-01
期刊: IEEE ROBOTICS AND AUTOMATION LETTERS
影响因子: 5.2
作者: [Vargas, Luis, Huang, He, Hu, Xiaogang]
通讯作者: Hu, Xiaogang
NSF-FR: Bidirectional Neural-Machine Interface for Closed-Loop Control of Prostheses
NCS-FO: Functional and neural mechanisms of integrating multiple artificial somatosensory feedback signals in prosthesis control
HCC: Medium: A novel neural interface for user-driven control of rehabilitation of finger individuation
CAREER: Robust Decoding of Neural Command for Real Time Human Machine Interactions
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