Identifying individual-specific gait signatures for stroke rehabilitation

识别中风康复的个体特定步态特征

• 批准号: 10389370
• 负责人: Taniel Solarnge Winner
• 金额: $ 4.68万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10389370
• 关键词: Address; Adverse effects; Affect; Ankle; Ataxia; Bilateral; Biomechanics; Case Series; Characteristics; Coin; Complex; Cross-Sectional Studies; Data; Descriptor; Development; Euclidean Space; Exposure to; Foot-drop; Future; Gait; Gait speed; Goals; Heterogeneity; Hip region structure; Impairment; Individual; Intervention; Joints; Kinetics; Knee; Knee joint; Knowledge; Learning; Limb structure; Literature; Lower Extremity; Maps; Measures; Mentors; Modality; Modeling; Muscle; Neural Network Simulation; Neuromechanics; Paresis; Phase; Physics; Rehabilitation therapy; Research; Research Personnel; Sampling; Stroke; Study Subject; System; Techniques; Testing; Time; Torque; Training; Variant; Walking; Work; ankle joint dorsiflexor; base; biomechanical model; chronic stroke; functional electrical stimulation; gait rehabilitation; gait symmetry; improved; inter-individual variation; kinematics; neuroregulation; post stroke; recurrent neural network; rehabilitation strategy; responders and non-responders; response; stroke rehabilitation; stroke survivor; support vector machine; theories; tool; treatment response; two-dimensional; walking speed

PROJECT SUMMARY/ABSTRACT Stroke gait deficits are complex and marked by adverse effects on kinematics, kinetics, gait symmetry, and inter- and intra- limb joint coordination across different phases of the gait cycle. One intervention simply cannot target the high inter-individual variability of deficits observed in post-stroke gait. Approximately 2/3 of stroke survivors have persistent gait impairments despite being discharged from rehabilitation, and one reason could be the lack of tailored rehabilitation approaches to address their individual-specific impairments. The development of tailored rehabilitation approaches, however, is limited by the lack of robust metrics to identify and analyze individual- specific differences in gait. The objective of this work is to develop a sensitive, data-driven, consistent characterization of gait using continuous, multi-joint gait dynamics. The dynamics of gait will be extracted from measured kinematics (joint angles) and used to develop individual-specific gait characterizations, which we coined the ‘gait signature.’ We will use these gait signatures to probe the mechanisms underlying stroke gait impairment using rehabilitation techniques, specifically Fast functional electrical stimulation (FastFES). FastFES is a gait rehabilitation intervention that targets ankle dorsiflexor muscles to address foot drop, and ankle plantarflexor muscles to improve ankle torque at push-off. The literature suggests that response to FastFES depends on the precise alignment between a specific muscle coordination deficit and the gait rehabilitation modality. This suggests that knowledge of an individual’s specific gait impairment before rehabilitation can predict their response to therapy. Since FastFES is known to target ankle deficits related to ankle push-off, I will probe this theory and evaluate whether gait signatures can encode ankle push-off corrections in response to a single session exposure to FastFES. I predict that stroke individuals with ankle-related push-off deficits will show the greatest response or change in their gait signature towards normative (able-bodied) gait. Preliminary findings show that gait signatures accurately discriminate between different stroke individuals. A noteworthy finding is that our gait signatures do not appear to cluster according to walking speed, leading to our hypothesis that gait signatures distinguish individual-specific differences in stroke gait corresponding to what we know about heterogeneity in stroke gait impairments. We aim to determine the functional biomechanical relevance of various clusters of gait signatures, and we will determine whether FastFES targets a specific cluster of individuals depending on the biomechanical features, characteristics, or deficits that they have. Furthermore, we will determine whether gait signatures before FastFES exposure can predict whether stroke-survivor will be a potential responder to FastFES. If successful, gait signatures will prove to be a robust marker of specific gait impairments and have important implications for the development of future tailored rehabilitation strategies for stroke survivors.

项目总结/摘要 中风步态缺陷是复杂的，并以对运动学、动力学、步态对称性和步态间的不良影响为特征。 和跨步态周期的不同阶段的肢体内关节协调。一次干预根本不能针对 在中风后步态中观察到的缺陷的个体间差异很大。大约2/3的中风幸存者 尽管从康复中心出院，但仍有持续的步态障碍，其中一个原因可能是缺乏 量身定制的康复方法，以解决他们的个人特定的障碍。定制化的发展 然而，康复方法受到缺乏强有力的指标来识别和分析个体的限制， 步态的具体差异。这项工作的目标是制定一个敏感的，数据驱动的，一致的 使用连续的多关节步态动力学来表征步态。步态的动力学将从 测量运动学（关节角度），并用于开发个人特定的步态特征，我们 创造了“步态特征”我们将使用这些步态特征来探测中风步态的潜在机制 使用康复技术，特别是快速功能性电刺激（FastFES）。FastFES 是一种步态康复干预，目标是踝关节背屈肌，以解决足下垂，踝关节 跖屈肌，以提高踝关节扭矩在推离。文献表明，对FastFES的反应 取决于特定肌肉协调缺陷和步态康复之间的精确对准 模态这表明，在康复前了解一个人的具体步态障碍， 预测他们对治疗的反应由于FastFES已知针对与踝关节蹬离相关的踝关节缺陷，我将 探索这一理论，并评估步态签名是否可以编码踝关节蹬离校正，以响应 单次会话暴露于FastFES。我预测患有踝关节相关推离障碍的中风患者 他们的步态特征对标准（健全）步态的最大反应或变化。初步调查结果 显示步态特征准确地区分不同中风个体。值得注意的发现是， 我们的步态特征似乎并没有根据步行速度聚集，这导致我们的假设， 签名区分中风步态中的个体特异性差异， 中风步态障碍的异质性。我们的目的是确定各种功能的生物力学相关性， 集群的步态签名，我们将确定是否FastFES目标的一个特定集群的个人 这取决于它们所具有的生物力学特征、特性或缺陷。此外，我们将 确定FastFES暴露前的步态特征是否可以预测中风幸存者是否会成为 FastFES的潜在应答者。如果成功的话，步态特征将被证明是一个强大的标志，具体步态 并对未来定制康复策略的发展具有重要意义， 中风幸存者