HCC: Medium: A novel neural interface for user-driven control of rehabilitation of finger individuation

HCC：中：一种新颖的神经接口，用于用户驱动的手指个性化康复控制

• 批准号: 2106747
• 负责人: Xiaogang Hu
• 金额: $ 80万
• 依托单位: University of North Carolina at Chapel Hill
• 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
• 起止时间: 2021-10-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106747&HistoricalAwards=false
• 关键词: HCC; Medium; novel; neural; interface

Following a stroke incident, a majority of stroke survivors lose the ability to use their hand to perform a variety of tasks despite months of therapy. In an effort to restore hand dexterity, advanced assistive devices (e.g., exoskeletons) have been developed. Unfortunately, only few of these novel devices have been used effectively by stroke survivors. One critical factor limiting user acceptance is the lack of reliable method that allows stroke survivors to intuitively control the device. The overarching objective of the project is to combine novel decoding of neurological signals that drive the muscles with a personalized musculoskeletal model of the upper limb to provide intuitive control of an assistive hand exoskeleton. The control strategy will be robust in handling different arm postures and movements. This personalized approach will improve hand functional performance in stroke survivors, with the overall goal of improving their ability to live independently. The computational approaches employed here will also produce a research tool to study human-robot interactions. The researchers will make the computational model available over online repository system, SimTK.org, as a simulation platform for other researcher working on hand function and control of rehabilitative devices. The project will provide educational and training opportunities. The research concepts will be integrated into existing courses. Summer projects incorporating the techniques will be offered to undergraduate and high school students and local school and community college instructors. Outreach programs will be developed to disseminate the proposed research outcomes to underrepresented students.The goal of this project is to develop a personalized hybrid (neural data-based and model-based) interface that combines the decoded neural command with a musculoskeletal model. The developed interface will be used to control a soft-hard hybrid exoskeleton to enable dexterous finger movements in stroke survivors. The research team will first develop a real-time neural decoding algorithm based on populational firing probability of the motoneurons, extracted from motor unit decomposition of high-density electromyographic (HD-EMG) signals. Through incorporation of binary neuron discharge events, the decoded neural drive signals will be robust to changes in muscle activity features, background noise, and motion artifact. The research team will then employ a personalized musculoskeletal model of the limb, which will be calibrated to the unique musculoskeletal structure and activation parameters of stroke survivors. The model-based controller will be able to compensate for limb posture, movement dynamics, and subject-specific impairments that could otherwise disturb the mapping between user input and desired output. Finally, the research team will evaluate the developed interface for control of an advanced hand exoskeleton, allowing users to control flexion or extension assistance independently for each digit. The assistive forces will reinforce beneficial muscle activation while compensating for abnormal activation patterns. Collectively, the outcomes will restore hand dexterity in stroke survivors, thereby enabling them to perform daily activities and live independently.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.

中风事件发生后，大多数中风幸存者失去了尽管经过数月的治疗，但大多数中风幸存者都无法使用手来执行各种任务。为了恢复手敏度，已经开发了先进的辅助设备（例如外骨骼）。不幸的是，中风幸存者有效地使用了这些新型设备中的很少。限制用户接受的一个关键因素是缺乏可靠的方法，该方法允许中风幸存者直观地控制设备。该项目的总体目的是将驱动肌肉的神经信号的新颖解码与上肢的个性化肌肉骨骼模型相结合，以提供对辅助手部外骨骼的直观控制。控制策略将在处理不同的手臂姿势和运动方面具有牢固的态度。这种个性化的方法将改善中风幸存者的手部功能性能，其总体目标是提高其独立生活的能力。这里采用的计算方法还将生成研究人类机器人相互作用的研究工具。研究人员将使计算模型可通过在线存储库系统Simtk.org获得，作为其他研究人员手工功能和康复设备控制的仿真平台。该项目将提供教育和培训机会。研究概念将集成到现有课程中。结合这些技术的夏季项目将提供给本科生和高中生以及当地学校和社区大学教师。将开发推出计划以将所提出的研究成果传播给代表性不足的学生。该项目的目的是开发一个个性化混合（基于神经数据的基于数据和模型）界面，该界面将解码的神经命令与肌肉骨骼模型相结合。开发的界面将用于控制软性杂种外骨骼，以使中风幸存者中的灵巧手指运动。研究团队将首先根据运动神经元的人口射击概率开发一种实时的神经解码算法，该算法是从高密度肌电图（HD-EMG）信号的运动单元分解中提取的。通过纳入二元神经元排出事件，解码的神经驱动信号将对肌肉活动特征，背景噪声和运动伪像的变化具有鲁棒性。然后，研究小组将采用个性化肢体的肌肉骨骼模型，该模型将校准为中风幸存者的独特肌肉骨骼结构和激活参数。基于模型的控制器将能够弥补肢体姿势，运动动力学和特定于主题的障碍，否则可能会干扰用户输入和所需输出之间的映射。最后，研究团队将评估开发的界面以控制高级手部外骨骼，使用户可以独立控制每个数字的屈曲或扩展帮助。辅助力将增强有益的肌肉激活，同时补偿异常激活模式。总的来说，结果将恢复中风幸存者中的手敏感，从而使他们能够进行日常活动并独立生活。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更广泛影响的审查标准通过评估来通过评估来支持的。

项目成果

Virtual Reality for Evaluating Prosthetic Hand Control Strategies: A Preliminary Report

用于评估假手控制策略的虚拟现实：初步报告

• DOI: 10.1109/embc46164.2021.9630555
• 发表时间: 2021
• 期刊: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC
• 作者: Xie, Jason;Hu, Xiaogang
• 通讯作者: Hu, Xiaogang

A generic neural network model to estimate populational neural activity for robust neural decoding

• DOI: 10.1016/j.compbiomed.2022.105359
• 发表时间: 2022-03
• 期刊: Computers in biology and medicine
• 影响因子: 7.7
• 作者: R. Roy;Feng Xu;D. Kamper;Xiaogang Hu

A Hand Exoskeleton for Stroke Survivors’ Activities of Daily Life

适用于中风幸存者日常生活活动的手部外骨骼

• DOI: 10.1109/embc46164.2021.9629805
• 发表时间: 2021
• 期刊: Proceedings of IEEE Engineering in Medicine and Biology Society
• 作者: Ghassemi, Mohammad;Kamper, Derek G.
• 通讯作者: Kamper, Derek G.

Adaptive Real-Time Decomposition of Electromyogram During Sustained Muscle Activation: A Simulation Study

持续肌肉激活过程中肌电图的自适应实时分解：模拟研究

• DOI: 10.1109/tbme.2021.3102947
• 发表时间: 2022
• 期刊: IEEE Transactions on Biomedical Engineering
• 影响因子: 4.6
• 作者: Zheng, Yang;Hu, Xiaogang
• 通讯作者: Hu, Xiaogang

Distribution of M-Wave and H-Reflex in Hand Muscles Evoked via Transcutaneous Nerve Stimulation: A Preliminary Report

经皮神经刺激诱发的手部肌肉中 M 波和 H 反射的分布：初步报告

• DOI: 10.1109/embc46164.2021.9630300
• 发表时间: 2021
• 期刊: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC
• 作者: Vargas, Luis;Baratta, John;Hu, Xiaogang
• 通讯作者: Hu, Xiaogang