Collaborative Research: HEBB: Human-Robot Enabled System to Induce Brain Behavior Adaptations

合作研究：HEBB：诱导大脑行为适应的人机驱动系统

• 批准号: 1935501
• 负责人: Carolynn Patten
• 金额: $ 64.64万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1935501&HistoricalAwards=false
• 关键词: Collaborative; Research; HEBB; Human; Robot

The overall research objective of this collaborative project is to create an embodied, intelligent robotic system that can induce meaningful long-term change in human motor function by providing personalized, adaptive feedback and noninvasive neural stimulation designed to induce desirable neuromotor plasticity. The motor behavior targeted for enhancement is plantarflexor power during the push-off phase of gait; stroke survivors often produce diminished plantarflexor power and rely instead on an inappropriate hip flexion "pull-off" compensation, thereby limiting the quality of their gait and quality of life. Personalized learning methods will be employed to model and optimize behavioral responses to changes in performance feedback provided by an intelligent mobile robotic coach, which will guide gait training. The project will lay the foundation to determine whether training based solely on principles of motor learning suffice to induce meaningful increases in plantarflexor power that are retained over time, or whether simultaneous targeted changes in brain excitability are required. This project advances the NSF mission to promote the progress of science and advance the national health by developing an adaptive motor learning algorithm embedded within an interactive mobile robot to induce meaningful long-term changes in human motor function through human-robot interaction. Broader impacts of the project include efforts to enhance research reproducibility and rigor, and to broaden participation in STEM for women, minorities, and persons with disabilities. The overall objective of this research is to create an embodied, intelligent system that provides personalized, adaptive feedback to induce neuromotor plasticity, mediate motor adaptation, and promote meaningful, lasting increases in plantarflexor power, which is diminished during walking in many stroke survivors. Three sets of human subject experiments are researched. The first will identify critical parameters of performance feedback that facilitate the desired behavioral change. The second will use a novel learning paradigm to model and optimize behavioral responses to changes in performance feedback provided by an intelligent robotic coach. The third will use single-pulse transcranial magnetic stimulation (TMS) and paired associative stimulation (PAS) to harness neuroplastic effects in humans such that desired behavioral changes induced by optimized feedback training are made persistent through Hebbian learning mechanisms. The envisioned system will involve bi-directional learning between the human and machine intelligences to determine how to control important, but subject-specific, variables critical for maintaining and promoting motor function across the life and health span. Understanding these bi-directional relationships within the context of neurorehabilitation may provide insights that can further advance human-robot teaming in a range of application domains, including healthcare, manufacturing, and personal transportation.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.

这个协作项目的总体研究目标是创建一个具体的，智能的机器人系统，可以通过提供个性化的，适应性的反馈和无创的神经刺激来引起人类运动功能的有意义的长期变化，旨在诱导理想的神经运动可塑性。在步态的推断阶段，针对增强的运动行为是足底力的力量。中风幸存者通常会产生plantarflexor的力量降低，而是依靠不适当的臀部屈曲“拉动”补偿，从而限制了其步态和生活质量的质量。个性化的学习方法将被用来建模和优化智能移动机器人教练提供的性能反馈变化的行为反应，这将指导步态训练。该项目将奠定基础，以确定是否仅基于运动学原理的培训足以引起随着时间的推移保留的有意义的增加，或者是否需要对大脑兴奋性的同时定向变化。该项目通过开发一种嵌入在交互式移动机器人中的自适应运动学习算法来促进科学进步并推进国家健康的任务，以通过人类机器人的互动引起人类运动功能的有意义的长期变化。该项目的更广泛的影响包括增强研究可重复性和严格性的努力，并扩大对妇女，少数民族和残疾人的STEM的参与。这项研究的总体目的是创建一个具体的，智能的系统，该系统提供个性化的，适应性的反馈，以诱导神经运动的可塑性，介导运动适应性，并促进有意义的，持久的plantarflexor功率，这在许多中风幸存者中行走时会减少。研究了三组人类主题实验。第一个将确定绩效反馈的关键参数，以促进所需的行为改变。第二个将使用新颖的学习范式来建模并优化智能机器人教练提供的性能反馈变化的行为反应。第三个将使用单脉冲经颅磁刺激（TMS）和配对的缔合刺激（PAS）来利用人类的神经塑性效应，以使通过HEBBIAN学习机制通过优化的反馈训练引起的所需的行为变化。设想的系统将涉及人与机器智能之间的双向学习，以确定如何控制重要但特定的变量对于维持和促进整个生活和健康范围内的运动功能至关重要。在神经居住的背景下了解这些双向关系可能会提供洞察力，可以进一步在包括医疗保健，制造业和个人运输在内的一系列应用领域中进一步推进人类机器人的团队。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和广泛的影响来评估CRETERIA的评估。