NSF/FDA SIR: Objective Assessment of Recovery during Post Stroke NeuroRehabilitation Therapy using Brain-Muscle Connectivity Network
NSF/FDA SIR: Objective Assessment of Recovery during Post Stroke NeuroRehabilitation Therapy using Brain-Muscle Connectivity Network
批准号:
2037878
负责人:
S Farokh Atashzar
金额:
$10.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31
中文摘要
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英文摘要
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.
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Perilaryngeal-Cranial Functional Muscle Network Differentiates Vocal Tasks: A Multi-Channel sEMG Approach
喉周颅功能肌肉网络区分声音任务:多通道 sEMG 方法
DOI:
10.1109/tbme.2022.3175948
发表时间:
2022
期刊:
IEEE Transactions on Biomedical Engineering
影响因子:
4.6
作者:
[O' Keeffe, Rory, Shirazi, Seyed Yahya, Mehrdad, Sarmad, Crosby, Tyler, Johnson, Aaron M., Atashzar, S. Farokh]
通讯作者:
Atashzar, S. Farokh
Linear versus Nonlinear Muscle Networks: A Case Study to Decode Hidden Synergistic Patterns During Dynamic Lower-limb Tasks
线性与非线性肌肉网络:解码动态下肢任务期间隐藏协同模式的案例研究
DOI:
10.1109/ner52421.2023.10123899
发表时间:
2023
期刊:
2023 11th International IEEE/EMBS Conference on Neural Engineering (NER
影响因子:
--
作者:
[O'Keeffe, Rory, Rathod, Vaibhavi, Shirazi, Seyed Yahya, Mehrdad, Sarmad, Edwards, Alexis, Rao, Smita, Atashzar, S. Farokh]
通讯作者:
Atashzar, S. Farokh
DOI:
10.1109/iros47612.2022.9981786
发表时间:
2022-07
期刊:
bioRxiv
影响因子:
--
作者:
[Tianyun Sun;Jacqueline Libby;J. Rizzo;S. F. Atashzar]
通讯作者:
Tianyun Sun;Jacqueline Libby;J. Rizzo;S. F. Atashzar
Discrete Windowed-Energy Variable Structure Passivity Signature Control for Physical Human-(Tele)Robot Interaction
用于物理人(远程)机器人交互的离散窗能量变结构无源信号控制
DOI:
10.1109/lra.2021.3064204
发表时间:
2021
期刊:
IEEE Robotics and Automation Letters
影响因子:
5.2
作者:
[Thudi, Smrithi, Atashzar, S. Farokh]
通讯作者:
Atashzar, S. Farokh
DOI:
10.1109/tro.2022.3158195
发表时间:
2022-10
期刊:
IEEE Transactions on Robotics
影响因子:
7.8
作者:
[N. Feizi;Rajnikant V. Patel;M. Kermani;S. F. Atashzar]
通讯作者:
N. Feizi;Rajnikant V. Patel;M. Kermani;S. F. Atashzar
共 16 条
NSF/FDA SIR: Robust, Reliable, and Trustworthy Regulatory Science Tool for Stroke Recovery Assessment using Hybrid Brain-Muscle Functional Coupling Analysis
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批准号:2229697
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项目类别:Standard Grant
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资助金额:$10.0万
-
财政年份:2022
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负责人:S Farokh Atashzar
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依托单位:
Collaborative Research: Modeling and Control of Non-Passive Networks with Distributed Time-Delays: Application in Epidemic Control
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批准号:2208189
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项目类别:Standard Grant
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资助金额:$39.53万
-
财政年份:2022
-
负责人:S Farokh Atashzar
-
依托单位:
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批准号:2031594
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项目类别:Standard Grant
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资助金额:$12.5万
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财政年份:2020
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负责人:S Farokh Atashzar
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项目类别:面上项目
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