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，并且由于服务老龄化社会的需求与可用的神经康复资源之间的不平衡，对医疗保健基础设施造成了很大的压力。因此，为加速恢复而开发的新型康复技术激增。尽管这些设备的成功开发，缺乏客观的标准，除了使用主观措施的临床研究提出了有争议的建议，包括机器人的几个设备。 为了满足对有效康复技术的需求，这个为期一年的NSF/FDA驻校学者项目专注于设计，实施和评估一种新颖，客观和强大的康复算法生物标志物，名为Delta CorticoMuscular Information Based Connectivity（D-CMiC）。所提出的算法量化的中枢神经系统（CNS）和周围神经系统（PNS）之间的连接，通过设计和实施的协议，同时测量从大脑和踝关节肌肉的受影响的恢复中风后患者的一面的电活动。 项目成果将产生一个关于恢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）的患者提供更有效的康复设备。 在教育影响方面，该项目将通过举办关于医学中新兴脑机接口（BCI）技术的研讨会和人机接口的本科生团队项目，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，实施和评估一个强大的中风恢复算法生物标志物，其量化CNS（使用脑电图（EEG））和PNS（使用高密度表面肌电图（HD-sEMG））之间的频谱时间神经生理学连接。该项目的动机是缺乏客观的标准和直接的神经生理学指标来量化中枢和外周神经系统之间的转换，以控制功能运动的康复的“真正”的疗效。将通过从恢复中的中风患者和健康受试者收集数据来分析所开发的D-CMiC指标的预测能力、精度和效率。独特的D-CMiC功能包括：（1）准确和客观地跟踪Delta/低频带中的皮质肌功能连接，这将对随机高频伪影具有鲁棒性，同时编码运动控制的3个时间阶段：准备，执行，放松;（2）通过融合频谱时间相似性测量来计算地建模皮质肌连通性，这将奖励持续的真阳性CNS-PNS连接，同时减少假阳性;以及（3）为第一个医疗器械开发工具（MDDT）奠定基础，以便对上市前康复器械进行系统、客观和透明的评价，符合FDA的使命。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。

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.