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: 10605158
• 负责人: Taniel Solarnge Winner
• 金额: $ 4.77万
• 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/10605158
• 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; Flexor; 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; Movement; 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; 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.

项目摘要/摘要 中风步态定义是复杂的，并且对运动学，动力学，步态对称性和间相的不利影响明显 和肢体内的关节协调，跨遇见周期的不同阶段。一种干预根本无法定位 在击球后步态中观察到的缺陷的高个体间变异性。大约2/3的中风幸存者 有持续的AIT障碍目的地被恢复出院，一个原因可能是缺乏 量身定制的康复方法来解决其个人特定的障碍。量身定制的发展 然而，康复方法受到缺乏可靠的指标来识别和分析个体的限制 步态的具体差异。这项工作的目的是开发一个敏感，数据驱动的，一致的 使用连续的多关节步态动力学对步态的表征。步态的动力学将从 测量的运动学（关节角度），用于发展个体特定的步态特征，我们 创造了“步态签名”。我们将使用这些GIT签名来探测中风步态的机制 使用康复技术的损害，特别是快速功能电​​刺激（Fastfes）。 fastfes 是一种步态康复干预措施，靶向脚踝背屈肌肉以解决脚部，脚踝 植物的肌肉可改善推断时的踝关节扭矩。文献表明对fastfes的反应 取决于特定的肌肉协调不足与步态康复之间的精度对齐 方式。这表明在康复之前了解一个人的特定ACUIT障碍 预测他们对治疗的反应。由于已知Fastfes的针对踝关节定义与踝关节推断有关，我将 探究该理论并评估攻击签名是否可以编码以响应一个 单个会话暴露于Fastfes。我预测，与脚踝相关的推断定义的中风个人将显示 其步态签名最大的反应或变化是正常（身体健全的步态）。初步发现 表明步态签名准确地区分了不同的中风个体。一个值得注意的发现是 我们的步态特征似乎并没有根据步行速度聚集，这导致了我们的假设 签名与我们所知道的相对应的中风的特定特定差异 中风步态障碍的异质性。我们旨在确定各种功能性生物力学相关性 聚集签名群，我们将确定Fastfes是否针对特定的个体群 取决于生物力学特征，特征或定义它们的特征。此外，我们会的 确定在接触Fastfes之前是否对齐签名能够预测中风 - 幸存者是否会成为 对快速夫人的潜在响应者。如果成功，步态签名将被证明是特定步态的强大标记 损害和对未来量身定制的康复策略的发展具有重要意义 中风存活。