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.

项目概要/摘要 中风步态缺陷很复杂，其特点是对运动学、动力学、步态对称性和内部相互作用产生不利影响。 步态周期不同阶段的肢体内关节协调是无法通过一种干预来实现的。 大约 2/3 的中风幸存者在中风后步态中观察到高度的个体间差异。 尽管已康复出院，但仍存在持续的步态障碍，原因之一可能是缺乏 量身定制的康复方法来解决其个人特定的障碍。 然而，由于缺乏强有力的指标来识别和分析个人康复方法，康复方法受到限制。 这项工作的目标是开发一种敏感的、数据驱动的、一致的步态差异。 使用连续的多关节步态动力学表征步态动力学将从中提取。 测量运动学（关节角度）并用于开发个体特定的步态特征，我们 创造了“步态特征”。我们将使用这些步态特征来探讨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）来治疗损伤。 是一种步态康复干预措施，针对踝关节背屈肌，以解决足下垂和踝关节问题 文献表明，FastFES 可以改善踝关节扭矩。 取决于特定肌肉协调缺陷和步态康复之间的精确对准 这表明在康复之前了解个人的特定步态障碍是可以的。 预测他们对治疗的反应 由于 FastFES 已知可以针对与踝关节推出相关的踝关节缺陷，我将 探究这一理论并评估步态特征是否可以编码脚踝推出校正以响应 我预测，患有踝关节推离缺陷的中风患者会出现单次暴露于 FastFES 的情况。 他们的步态特征对规范（健全）步态的最大反应或变化。 表明步态特征可以准确地区分不同的中风个体。 我们的步态特征似乎并不根据步行速度进行聚类，这导致我们假设步态 特征区分了与我们所知相对应的中风步态的个体特异性差异 我们的目标是确定各种功能生物力学相关性。 步态特征集群，我们将确定 FastFES 是否针对特定的个体集群 取决于他们的生物力学特征、特征或缺陷。此外，我们会。 确定 FastFES 暴露之前的步态特征是否可以预测中风幸存者是否会成为中风幸存者 如果成功，步态特征将被证明是特定步态的有力标记。 损伤，对于制定未来定制的康复策略具有重要意义 中风幸存者。