SCH: Smart User-Effective Data-Enabled (SUEDE) Shoe for Ankle Injury Prevention

拟议的研究与公共卫生有关，并与NIAMS的使命保持一致，因为它 解决了提高预防踝关节扭伤的有效性的实质性需求，这是最重要的 常见的肌肉骨骼损伤，可显著影响身体活动和生活质量。而 外部被动支持，如踝关节包扎和支具，是最广泛使用的方法， 防止踝关节扭伤，长期使用会使患者过度依赖被动和持续的 支持，从而导致踝关节肌肉和软组织萎缩。这种方法不仅限制了 内翻-外翻运动，而且还有背屈-跖屈运动，这反过来又可能改变自然的 下肢生物力学该项目旨在研究一种独特的智能鞋系统， 工程、计算和行为科学的科学解决方案，以克服这些限制， 为有踝关节损伤风险的个人提供增强的支撑。我们的具体目标是：（1）设计和 实现一种智能鞋系统，该系统集成了对生物力学数据的鲁棒的实时估计， 活动识别来自具有软致动器的可穿戴传感器， 踝关节支具;（2）量化和建模健康个体的踝关节刚度和足部负荷轨迹 以及有踝关节扭伤风险的人;（3）整合损伤预测算法和 闭环反馈控制器，其提供主动踝关节支撑以防止扭伤;以及（4）改善 为自由生活开发算法，并设计一个直观的移动的用户界面， 实时汇总伤害风险指标。我们将验证和评估所提出的智能鞋系统 通过与临床合作伙伴密切合作，确保系统针对最佳临床 一体化的思想。智能鞋系统具有临床意义，因为它将使临床医生更好地 了解踝关节力学及其与各种体育活动中踝关节损伤风险的相关性 并帮助他们及时向用户提供有效的总结性反馈，以促进他们的 坚持踝关节损伤预防策略。成功开发的系统和严谨的 评估其以患者和临床为中心的感知效用将为后续临床研究奠定基础。 专门旨在研究干预措施对保留/促进踝关节功能的长期影响的试验 健康和提高行为坚持临床建议。 相关性（参见说明）： 这项研究解决了提高预防踝关节扭伤的有效性的实质性需求， 引入智能鞋系统，根据需要主动支撑脚踝，而不会妨碍自然运动。 踝关节运动，并提供直观的用户界面与伤害风险指标，以促进用户遵守 临床处方这一解决方案预计将大大提高目前的有效性， 被动踝关节支撑或胶带的做法，并有助于促进踝关节健康的长期目标。

The proposed research is relevant to public health and well aligned with the mission of NIAMS because it addresses the substantial need to improve effectiveness in prevention of ankle sprains, one of the most common musculoskeletal injuries that can significantly impact physical activity and quality of life. While external passive supports, such as ankle taping and bracing, are the most widely used approaches to prevent ankle sprains, their long-term use makes patients overly reliant on the passive and constant support, which leads to ankle muscle and soft tissue atrophy. Furthermore, this approach not only restricts inversion-eversion motion but also dorsiflexion-plantarflexion motion, which in turn may alter natural lower-extremity biomechanics. This project seeks to study a unique smart shoe system, using integrated scientific solutions of engineering, computing and behavioral science, to overcome these limitations and provide enhanced support for individuals at risk of ankle injury. Our specific aims are: (1) to design and implement a smart shoe system that integrates robust, real-time estimation of biomechanical data and activity recognition from wearable sensors with soft actuators capable of actively adjusting the stiffness of the ankle brace; (2) to quantify and model ankle stiffness and foot loading trajectory in healthy individuals as well as in people at risk of ankle sprains; (3) to integrate an injury prediction algorithm and a closed-loop feedback controller that provides active ankle support to prevent sprains; and (4) to refine the developed algorithms for free-living use and design an intuitive mobile user interface that provides summative injury risk metrics in real-time. We will validate and evaluate the proposed smart shoe system by closely engaging with clinical partners to ensure the system is tailored toward optimal clinical integration in mind. The smart shoe system is clinically significant because it will allow clinicians to better understand foot-ankle mechanics and their correlation to ankle injury risk during various physical activities and help them provide effective and summative feedback to the users in a timely manner to promote their adherence to ankle injury prevention strategies. Successful development of the system and rigorous assessment of its patient- and clinic-centered perceived utility will lay the groundwork for follow-up clinical trials specifically aimed at investigating the long-term effect of interventions on preserving/promoting ankle health and enhancing behavioral adherence to clinical recommendations. RELEVANCE (See instructions): This research addresses the substantial need to improve effectiveness in prevention of ankle sprains by introducing a smart shoe system that actively supports the ankle as needed without hindering natural ankle motion and provides an intuitive user interface with injury risk metrics to promote user adherence to clinical prescriptions. This solution is expected to substantially enhance the effectiveness of the current practice of passive ankle bracing or taping and contribute to the long-term goal of promoting ankle health.