NSF-FR: Bidirectional Neural-Machine Interface for Closed-Loop Control of Prostheses

NSF-FR：用于假肢闭环控制的双向神经机器接口

• 批准号: 2319139
• 负责人: Xiaogang Hu
• 金额: $ 399.96万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2028-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2319139&HistoricalAwards=false
• 关键词: NSF; FR; Bidirectional; Neural; Machine

Humans can control their limbs to perform a variety of daily tasks with great precision and remarkable adaptability in unpredictable environments, thanks to our cognitive capacity and physical characteristics. People with disabilities could rely on assistive robots that have similar functional capabilities of real limbs, yet people find it difficult to use on a daily basis, partly because the interfaces are unnatural and unintuitive. The objective of this project is to understand the neural and cognitive processes brought to bear during daily tasks, such as reaching and grasping, and to establish natural and nature-inspired approaches that allow the user and the machine (the artificial limb) to communicate. The research outcomes will reduce motor disability and improve quality of life of individuals with physical disabilities. The developed approaches can also enable intuitive control of assistive robots in medical, industrial, and military applications. Summer projects and outreach events, incorporating the proposed techniques, will be offered to undergraduate students in minority-serving universities and local K-12 students, specifically targeting underrepresented students. The research team will organize workshops at national conferences to disseminate research findings and facilitate broader collaborations. Certificate and credential programs will be offered through online learning platforms. Research outcomes will also be presented to local and regional patient support groups and national clinical-oriented conferences so as to disseminate state-of-the-art research development to end users.The goal of this project is to develop and evaluate a biomimetic human-centric neural-machine interface system, which incorporates outward (efferent) and inward (afferent) directed signals for the control of assistive robots. The system will allow individuals with disabilities to interact with their assistive robots as they use their biological limbs. If successful, it will provide a robust and effective model for intuitive interaction of human-machine systems for application to a broader variety of health and industrial applications, and finally overcome the problem of intuitive control of assistive devices in individuals with disability. The research team will strategically integrate research threads that address critical barriers for human-robot integration: Thread 1 will develop implantable and wearable electrode platforms for neural recording and neural stimulation. Thread 2 will understand fundamental principles of neural encoding of artificial sensation and establish biomimetic sensory encoding strategies. Thread 3 will develop an integrated shared control framework for dexterous control of robotic hands. Thread 4 will collectively address the functional integration of closed-loop robotic systems for perceptual motor control. The research team will integrate the proposed techniques, closing the loop between artificial sensing and actuation of the robot and the perception and control authority of the human, examining the adaptability and robustness of the closed-loop human-machine systems. Collectively, the research project can generate transformative outcomes that can blur the boundary between humans and assistive robots, allow end-users to fully leverage the functionality of advanced robots, and promote the development of next-generation neural-machine interfaces and assistive robots.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.

由于我们的认知能力和身体特征，人类可以控制四肢，以在无法预测的环境中执行各种日常任务。残疾人可以依靠具有相似功能能力的真实四肢功能的辅助机器人，但人们每天都很难使用，部分原因是界面是不自然和不直觉的。该项目的目的是了解在日常任务中所带来的神经和认知过程，例如到达和掌握，并建立允许用户和机器（人工肢体）交流的自然和自然风格的方法。研究成果将减少运动障碍并改善身体残障人士的生活质量。开发的方法还可以实现对医疗，工业和军事应用中辅助机器人的直观控制。夏季项目和外展活动（结合了拟议的技术）将为少数族裔服务大学和当地K-12学生的本科生提供，特别针对代表性不足的学生。研究团队将在国家会议上组织研讨会，以传播研究发现并促进更广泛的合作。证书和凭据计划将通过在线学习平台提供。研究成果还将提交给地方和区域性患者支持小组和国家临床导向的会议，以传播最终用户的最终研究开发。该项目的目的是开发和评估一个生物模仿的人类以人为中心的神经机器界面系统，该系统融合了（受（Fafferent）以及（亲和力）的辅助机器人，该系统融合了（afferent（受afferent）（受（Fafferent）（afferent（受afferent））。该系统将允许残疾人在使用生物肢体时与辅助机器人进行互动。如果成功的话，它将为人机系统的直观相互作用提供一个可靠的有效模型，以应用于更广泛的健康和工业应用，并最终克服了残疾人对辅助设备的直观控制问题。研究团队将战略性地整合研究线程，以解决人类机器人整合的关键障碍：线程1将开发可植入和可穿戴的电极平台，用于神经记录和神经刺激。线程2将了解人工感觉的神经编码的基本原理，并建立仿生的感觉编码策略。线程3将开发一个集成的共享控制框架，用于灵巧控制机器人手。线程4将集体解决用于感知电机控制的闭环机器人系统的功能集成。研究团队将整合提出的技术，结束机器人的人工传感和驱动之间的循环，以及人类的感知和控制权，检查了闭环人机系统的适应性和鲁棒性。总的来说，研究项目可以产生变革性的结果，使人与辅助机器人之间的边界模糊，使最终用户能够充分利用高级机器人的功能，并促进下一代神经机器人界面和辅助机器人的发展。该奖项颁发了NSF的法定任务，并反映了通过评估企业的支持者的支持者，并已被评估范围众所周知，并构成了基础的依据。