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

这个合作项目的总体研究目标是创建一个具体化的智能机器人系统，通过提供个性化的、自适应的反馈和非侵入性的神经刺激来诱导理想的神经运动可塑性，从而导致人类运动功能的有意义的长期变化。旨在增强的运动行为是在步态推出阶段的踝屈肌力；中风幸存者通常会产生踝屈肌力减弱，转而依赖不适当的髋屈曲“拉离”补偿，从而限制他们的步态质量和生活质量。个性化的学习方法将被用来建模和优化对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，以确定仅基于运动学习原则的训练是否足以诱导随着时间的推移保持的有意义的植物屈肌力量的增加，或者是否需要同时有针对性地改变大脑的兴奋性。该项目通过开发嵌入到交互式移动机器人中的自适应运动学习算法来推进NSF促进科学进步和促进国民健康的使命，通过人与机器人的交互来诱导人类运动功能的有意义的长期变化。该项目的更广泛影响包括努力提高研究的可重复性和严谨性，并扩大妇女、少数群体和残疾人参与科技教育管理的范围。这项研究的总体目标是创建一个具体化的、智能的系统，提供个性化的自适应反馈，以诱导神经运动可塑性，调节运动适应，并促进有意义的、持久的足屈肌力量的增加，许多中风幸存者在行走时会减少这种力量。研究了三组人体受试者实验。第一个将确定有助于实现所需行为改变的绩效反馈的关键参数。第二个将使用一种新的学习范式来建模和优化对智能机器人教练提供的性能反馈变化的行为反应。第三项研究将使用单脉冲经颅磁刺激(TMS)和成对联想刺激(PAS)来利用人类的神经可塑性效应，以便通过Hebbian学习机制使优化反馈训练引起的期望行为变化持久。设想的系统将涉及人类和机器智能之间的双向学习，以确定如何控制重要的、但特定于对象的变量，这些变量对于在整个生命和健康周期内维持和促进运动功能至关重要。在神经康复的背景下了解这些双向关系可能会提供见解，进一步推动人-机器人在一系列应用领域的合作，包括医疗保健、制造和个人交通。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.