NSF/FDA SIR: Objective Assessment of Recovery during Post Stroke NeuroRehabilitation Therapy using Brain-Muscle Connectivity Network

中风是运动障碍的主要原因，由于服务老龄化社会的需求与现有神经康复资源之间的不平衡，中风给医疗保健基础设施带来了巨大压力。因此，为加速康复而生产的新型康复技术激增。尽管这些设备的成功发展，除了使用主观测量的临床调查之外，缺乏客观标准，对包括机器人在内的几种设备提出了有争议的建议。为了满足对有效康复技术的需求，这个为期一年的NSF/FDA驻场学者项目专注于设计、实施和评估一种新的、客观的、健壮的康复算法生物标志物，名为Delta皮质肌肉信息连接（D-CMiC）。该算法通过设计和实现一种同时测量脑电活动的方案来量化中枢神经系统（CNS）和外周神经系统（PNS）之间的连通性。项目成果将产生一个关于康复的神经生理学的科学愿景，并加快为中风以外的一系列神经系统疾病（如帕金森病、原发性震颤和共济失调）患者提供更有效的康复设备。在教育方面，该项目将通过举办关于医学新兴脑机接口（BCI）技术的研讨会和人机接口的本科团队项目，创造一个独特的跨学科教育环境，重点是在代表性不足的群体中促进STEM活动。该项目的目标是设计、实施和评估卒中恢复的稳健算法生物标志物，该标志物量化CNS（使用脑电图（EEG））和PNS（使用高密度表面肌电图（HD-sEMG））之间的光谱时间神经生理连接。该项目的动机是缺乏客观标准和直接的神经生理学指标来量化康复的“真实”功效，即中枢和周围神经系统之间的转换来控制功能运动。开发的D-CMiC指标的预测能力、精度和效率将通过收集脑卒中康复患者和健康受试者的数据进行分析。独特的D-CMiC特征包括：(1)准确、客观地跟踪Delta/低频波段的皮质肌肉功能连接，在编码运动控制的3个时间阶段：准备、执行、放松时，对随机高频伪像具有鲁棒性；(2)通过融合光谱时间相似性测量对皮质肌肉连接进行计算建模，这将奖励持续的真阳性CNS-PNS连接，同时减少假阳性；(3)建立首个医疗器械开发工具（MDDT）的基础，用于对上市前康复器械进行系统、客观和透明的评估，与FDA的使命保持一致。该奖项反映了美国国家科学基金会的法定使命，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。

Stroke is the leading cause of motor disabilities and places high pressure on healthcare infrastructures due to the imbalance between the need for serving an aging society and available neurorehabilitation resources. Thus, there has been a surge in the production of novel rehabilitative technologies for accelerating recovery. Despite the successful development of such devices, lack of objective standards besides clinical investigations using subjective measures have made controversial recommendations regarding several devices, including robots. To address the need for effective rehabilitative technologies, this one year NSF/FDA Scholar-in-Residence project is focused on the design, implementation, and evaluation of a novel, objective, and robust algorithmic biomarker of recovery, named Delta CorticoMuscular Information-based Connectivity (D-CMiC). The proposed algorithm quantifies the connectivity between the central nervous system (CNS) and the peripheral nervous system (PNS) by designing and implementing a protocol for simultaneously measuring electrical activity from the brain and an ankle muscle on the affected side of recovering post-stroke patients. Project outcomes will produce a scientific vision regarding the neurophysiology of recovery and expedite availability of more effective rehabilitation devices to patients for a range of neurological disorders beyond stroke (such as Parkinson’s disease, Essential Tremor and Ataxia). For educational impact, the project will generate a unique transdisciplinary educational environment by conducting workshops regarding emerging Brain-Computer Interface (BCI) technologies in medicine and undergraduate team projects for human-machine interfacing, with a focus on promoting STEM activities within underrepresented groups.The goal of this project is to design, implement, and evaluate a robust algorithmic biomarker of stroke recovery, which quantifies the spectrotemporal neurophysiological connectivity between the CNS (using electroencephalography (EEG)) and PNS (using high-density surface electromyography (HD-sEMG)). The project is motivated by the lack of objective standards and direct neurophysiological metrics for quantifying the “true” efficacy of rehabilitation in terms of the translation between central and peripheral nervous systems to control functional movements. The predictive capability, precision, and efficiency of the developed D-CMiC metric will be analyzed by collecting data from recovering stroke patients and healthy subjects. Unique D-CMiC features include: (1) accurately and objectively tracking corticomuscular functional connectivity in the Delta/low frequency band, which will be robust to stochastic high-frequency artifacts while encoding the 3 temporal phases of motor control: preparation, execution, relaxation; (2) computationally modeling of corticomuscular connectivity through the fusion of spectrotemporal similarity measures, which will reward persistent true-positive CNS-PNS connections while diminishing false-positives; and (3) building the basis for the first medical device development tool (MDDT) for the systematic, objective, and transparent evaluation of pre-market rehabilitation devices, aligned with the FDA’s mission.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.