Asymmetric Walking Protocol for Optimal Post-ACL Reconstruction Rehabilitation

用于最佳 ACL 重建后康复的不对称行走方案

• 批准号: 10693894
• 负责人: Kristin Morgan
• 金额: $ 12.35万
• 依托单位: UNIVERSITY OF CONNECTICUT STORRS
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10693894
• 关键词: Adoption; Algorithms; Analysis of Variance; Biomechanics; Biomedical Engineering; Biomedical Research; Caring; Clinic; Clinical; Comparative Study; Computer Models; Data; Data Analytics; Dedications; Development; Effectiveness; Evaluation; Functional disorder; Future; Gait; Gait speed; Goals; Health Care Costs; Impairment; Individual; Injury; Institution; Intervention; Knee; Knee Osteoarthritis; Laboratories; Limb structure; Machine Learning; Measures; Mechanics; Medicine; Mentored Research Scientist Development Award; Mentors; Mentorship; Modeling; Monitor; Orthopedics; Outcome; Participant; Patients; Pattern; Performance; Persons; Physical therapy; Population; Protocols documentation; Public Health; Quality of life; Rehabilitation Outcome; Rehabilitation therapy; Research; Research Activity; Research Personnel; Research Training; Resources; Stroke; Testing; Therapeutic; Time; Training; Training Activity; Translating; Translational Research; Traumatic Arthropathy; United States; United States National Institutes of Health; Walking; Work; algorithm development; anterior cruciate ligament injury; anterior cruciate ligament reconstruction; biomechanical model; career; clinical translation; comorbidity; comparative; effectiveness evaluation; gait examination; gait rehabilitation; improved; innovation; joint loading; mechanical load; neuromuscular; novel; novel therapeutic intervention; novel therapeutics; primary outcome; recruit; response; restoration; return to sport; signal processing; simulation; skills; success

Project Abstract The primary goal of the proposed work is to provide the PI with advanced biomedical research training, outstanding mentorship, and protected time to become a leading independent researcher in post-anterior cruciate ligament reconstruction (ACLR) rehabilitation. A significant consequence of the approximately 250,000 anterior cruciate ligament injuries that occur annually in the United States is that unresolved neuromuscular impairments often lead to the development of detrimental knee osteoarthritis and other debilitating comorbidities. Despite extensive rehabilitation, protracted deficits in gait mechanics remain and directly contribute to detrimental knee loading. Yet, a promising finding from stroke research is that an asymmetric walking protocol can disrupt maladaptive gait mechanics and lead to the adoption of new, healthy gait patterns. While the success of the asymmetric protocol in correcting adverse gait patterns is often assessed by the magnitude of the between-limb gait speed perturbation, this novel intervention to our knowledge has never been employed in post-ACLR patients. Thus, I will employ experimental gait analysis, computational modeling, biosignal processing, and machine learning to restore healthy post-ACLR gait mechanics and reduce knee loading as outlined by the following aims: Aim 1. Evaluate the effectiveness of asymmetric walking protocol gait perturbation magnitudes in restoring healthy gait in post-ACLR individuals. Aim 2. Develop patient-specific models to evaluate the impact asymmetric walking protocol gait perturbation magnitude has on reducing detrimental knee loading in post-ACLR individuals. Aim 3. Generate personalized data-driven clinical algorithm to rapidly and non-invasively predict knee loads in a clinical setting. The results of this research will yield new therapeutic interventions and treatment guidance to improve post- ACLR rehabilitation outcomes. The successful execution of the proposed work will involve a strong team of interdisciplinary researchers with skills in signal processing, machine learning, medicine, biomedical engineering, computational modelling, and physical therapy. The PI has assembled a dynamic team with a superb reputation for mentoring others and they will provide her with research guidance in addition to career and professional development direction and support. This mentorship combined with strong institutional support, state-of-the-art resources, and facilities, and dedicated protected time will allow her to successfully perform the research and training activities outlined in her K01 Mentored Research Scientist Development Award.

项目摘要 拟议工作的主要目标是为PI提供先进的生物医学研究培训， 杰出的指导和受保护的时间，成为后领先的独立研究员 交叉韧带重建（ACLR）康复。大约25万 在美国每年发生的前交叉韧带损伤是未解决的神经肌肉 损害通常会导致有害的膝关节骨关节炎和其他令人衰弱 合并症。尽管进行了广泛的康复，但步态力学中持久的缺陷仍然存在，直接 导致有害的膝盖负荷。然而，中风研究的一个有希望的发现是不对称的 步行方案会破坏适应不良的步态力学，并导致采用新的健康步态模式。 尽管不对称方案在纠正不良步态模式方面的成功通常由 LIMB之间的步态速度扰动的大小，这种新颖的干预从来没有 受雇于后ACLR患者。因此，我将采用实验步态分析，计算建模， 生物信号处理和机器学习以恢复健康后步态力学并减少膝盖 按照以下目的概述的加载： 目标1。评估不对称步行方案步态扰动的有效性 恢复后ACLR个体的健康步态。 目标2。开发特定于患者的模型来评估影响不对称步行方案步态 扰动幅度具有减少ACLR后个体中有害膝关节的负荷。 目标3。生成个性化数据驱动的临床算法，以快速和无创地预测膝盖 在临床环境中负载。 这项研究的结果将产生新的治疗干预措施和治疗指导，以改善后 ACLR康复结果。 拟议的工作的成功执行将涉及一支由跨学科研究人员组成的团队 信号处理，机器学习，医学，生物医学工程，计算建模和 物理疗法。 PI召集了一个充满活力的团队，在指导他人方面享有很高的声誉 除职业和专业发展方向外，他们还将为她提供研究指导 支持。这种指导结合了强大的机构支持，最先进的资源和设施， 专门的受保护时间将使她能够成功地进行研究和培训活动 在她的K01指导研究科学家发展奖中。