From post-stroke assistance to rehabilitation: Neuromuscular adaptations to walking with a soft robotic exosuit

从中风后援助到康复：神经肌肉适应软机器人外装行走

• 批准号: 10471196
• 负责人: Ashley Collimore
• 金额: $ 4.28万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-16 至 2023-08-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10471196
• 关键词: Affect; Ankle; Biomechanics; Characteristics; Chronic; Clinical assessments; Complement; Development Plans; Electric Stimulation; Evaluation; Financial compensation; Gait; Impairment; Individual; Isometric Contraction; Laboratories; Laboratory Research; Lead; Limb structure; Link; Locomotion; Lower Extremity; Measures; Mentors; Methods; Muscle; Muscle Weakness; Paresis; Participant; Patients; Persons; Predictive Factor; Process; Protocols documentation; Reaction; Recovery; Rehabilitation device; Rehabilitation therapy; Research Project Grants; Robotics; Self-Help Devices; Specificity; Speed; Standardization; Stroke; Technology; Testing; Training; Translational Research; Visit; Volition; Walking; Work; biomechanical test; exosuit; gait rehabilitation; hemiparesis; improved; indexing; locomotor control; motor control; multimodality; muscle strength; nervous system disorder; neuromuscular; neuromuscular rehabilitation; neuroregulation; novel; post stroke; predicting response; relating to nervous system; research clinical testing; skills; spatiotemporal; synergism; treadmill; treatment response; walking speed

PROJECT SUMMARY Stroke affects approximately 800,000 people annually, resulting in hemiparesis and characteristically slow, asymmetric walking. Our team has developed and extensively studied a novel soft-robotic exosuit that improves paretic propulsion and walking speed by augmenting the function of the paretic limb during use. These findings demonstrate the value of the soft robotic exosuit as an assistive device, but its rehabilitative potential remains unclear. Recovery of walking speed is important for both clinicians and patients; however, improvements in walking speed may be achieved via different rehabilitation processes, ranging from propulsion recovery (e.g., propulsion symmetry) to compensation (e.g., a reliance on nonparetic propulsion). Ground reaction force analyses have been used to differentiate between propulsion recovery and compensation but lack specificity in identifying impairments in the neuromuscular control of the lower limb muscles during walking and improvements in control with rehabilitation. To determine the rehabilitative potential of REAL, we will combine measures of neuromuscular control with conventional measures of locomotor propulsion and speed to characterize its rehabilitation processes (i.e., recovery vs. compensation) and neuromuscular predictors. For this project, we will study the effects of repeated sessions of Robotic Exosuit Augmented Locomotion (REAL) gait training, a standardized gait retraining protocol developed by our laboratory to leverage the gait- restorative effects of soft robotic exosuits to retrain faster walking after stroke by way of improved paretic propulsion. More specifically, 22 chronic (>6 months) post-stroke participants will complete three sessions of REAL gait training. To characterize the rehabilitation potential of REAL (Aim 1) and predictors of a REAL therapeutic response (Aim 2), at each visit we will conduct multi-modal evaluations that combine standard biomechanical and clinical assessments (i.e., propulsion and speed) with distinct measures of neuromuscular control known to be sensitive to post-stroke gait impairments. A multi-modal evaluation approach that combines measures of neuromuscular control with standard clinical and biomechanical evaluations provides the best opportunity to understand the link between post-stroke walking impairment and recovery with REAL training. This research project complements my development plan by providing an opportunity to work with my mentoring team to apply and enhance my skills in measuring, analyzing, and understanding neuromuscular control post-stroke, ultimately preparing me to lead a translational research laboratory developing and evaluating rehabilitation devices to improve walking ability in people with neurological disorders.

项目摘要 中风每年影响大约80万人，导致轻偏瘫和典型的缓慢， 不对称行走我们的团队已经开发并广泛研究了一种新型的软机器人外装， 通过在使用过程中增强麻痹肢体的功能来改善麻痹推进和行走速度。 这些发现证明了软机器人外装作为辅助设备的价值，但其康复 潜力尚不清楚。 步行速度的恢复对临床医生和患者都很重要;然而， 步行速度可以通过不同的康复过程来实现，从推进恢复（例如， 推进对称性）到补偿（例如，依赖于非麻痹性推进）。地面反作用力 虽然已经有人用分析的方法来区分推进力的恢复和补偿，但是这种方法缺乏针对性 在识别行走过程中下肢肌肉的神经肌肉控制障碍方面， 通过康复改善控制。为了确定真实的的康复潜力，我们将 将神经肌肉控制的联合收割机措施与运动推进和速度的常规措施相结合 以表征其康复过程（即，恢复与补偿）和神经肌肉预测因子。 在这个项目中，我们将研究机器人Exosuit Augmented的重复会话的效果 运动（真实的）步态训练，由我们实验室开发的标准化步态再训练协议， 利用软机器人运动服的步态恢复效果，通过以下方式重新训练中风后更快的行走： 改善麻痹性推进。更具体地说，22名慢性（>6个月）卒中后参与者将 完成三次真实的的步态训练。表征真实的的康复潜力（目的1） 和真实的反应的预测因子（目标2），在每次访视时，我们将进行多模式 结合联合收割机标准生物力学和临床评估的评估（即，推进力和速度） 已知神经肌肉控制的不同测量对中风后步态损伤敏感。一 多模式评估方法，将神经肌肉控制措施与标准临床 生物力学评估提供了最好的机会来了解中风后 步行障碍和恢复与真实的的训练。 这个研究项目补充了我的发展计划，提供了一个机会，与我的工作。 指导团队应用并提高我在测量、分析和理解神经肌肉方面的技能 控制中风后，最终准备我领导一个转化研究实验室发展， 评估康复设备，以提高神经系统疾病患者的行走能力。