Real-Time Model-Based Gait Retraining for Knee Osteoarthritis Rehabilitation

描述（由申请人提供）：本申请的长期目标是开发一种新的康复方法来减缓膝关节骨关节炎的进展，从而改善数以百万计的患者的功能并减少疼痛。与传统的康复方法不同，该方法是定量的，将患者特定的计算机模型与实验步态分析相结合。计算机模型被用来预测改变但看起来自然的步态模式，以减少有害的膝盖负荷。随后的步态分析和实时视觉反馈被用于训练患者，使其与计算机模型预测的膝关节负荷相匹配。步态再训练的特定负荷是膝关节外内收扭矩（即，有助于内侧筋膜室力的时刻），因为该负荷是膝关节骨关节炎严重程度和进展的有力指标。在没有实时视觉反馈的情况下，对两名受试者首次应用该入路，内收扭矩曲线的两个峰值均减少了50%，与胫骨高位截骨手术的结果相当，但没有手术干预。为了研究这一长期目标的可行性，我们建议在一项涉及10名早期膝关节骨关节炎患者的可行性研究中追求三个具体目标：具体目标1：用患者特异性计算模型预测是否存在类似的步态改变，可以显著降低每个患者的双膝内收扭矩峰值。具体目标2：利用基于实时模型的视觉反馈，确定患者在进行8次步态再训练后，是否能显著降低膝关节内收扭矩。具体目标3：确定在步态再训练计划完成后，是否可以维持至少一个月的显著膝关节内收扭矩降低。如果成功，提出的方法可能允许定制步态再训练用于减缓膝关节骨关节炎的进展，甚至作为预防措施。最终结果可能是数以百万计的患者疼痛减轻，功能改善，他们可以推迟甚至避免膝关节置换手术。膝关节骨性关节炎在美国折磨着数百万人，它会引起疼痛，并限制人们进行重要的日常活动，如走路和爬楼梯。利用患者特定的计算机模型和实验步态分析，本研究旨在开发一种新的康复方法来减缓疾病的进展。如果成功，该方法将允许许多患者推迟甚至可能避免将来需要进行膝关节置换手术。

DESCRIPTION (provided by applicant): The long term objective of this application is to develop a novel rehabilitation approach to slow the progression of knee osteoarthritis, resulting in improved function and reduced pain for millions of patients. Unlike traditional rehabilitation approaches, the proposed approach is quantitative, combining patient-specific computer models with experimental gait analysis. The computer models are used to predict altered yet natural looking gait patterns that reduce detrimental knee loads. Subsequent gait analysis with real-time visual feedback is then used to train the patient to match the knee loads predicted by the computer model. The specific load targeted by gait retraining is the external knee adduction torque (i.e., the moment that contributes to medial compartment force), since this load is a strong indicator of knee osteoarthritis severity and progression. Initial application of the approach to two subjects but without real-time visual feedback yielded reductions as large as 50% in both peaks of the adduction torque curve, comparable to the results of high tibial osteotomy surgery but without surgical intervention. To investigate the feasibility of this long term objective, we propose to pursue three specific aims in a feasibility study study involving 10 patients with early knee osteoarthritis: Specific aim 1: Predict with a patient-specific computational model whether similar gait modifications exist for each patient that will significantly reduce both knee adduction torque peaks. Specific aim 2: Determine whether patients can achieve significant knee adduction torque reductions after eight gait retraining sessions using real-time model-based visual feedback. Specific aim 3: Determine whether significant knee adduction torque reductions can be maintained for at least one month following the completion of the gait retraining program. If successful, the proposed approach may permit customized gait retraining to be used to slow the progression of knee osteoarthritis or even as a preventative measure. The end result could be millions of patients with decreased pain and improved function who can delay or even avoid knee replacement surgery. Knee osteoarthritis afflicts millions of people in the United States, causing pain and limiting the ability to perform important daily activities such as walking and stair climbing. Using patient-specific computer models and experimental gait analysis, this research seeks to develop a novel rehabilitation approach to slow the progression of the disease. If successful, the approach would allow many patients to delay or possibly even avoid the need for knee replacement surgery in the future.