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

SCH：用于预防脚踝损伤的智能用户有效数据启用 (SUEDE) 鞋

• 批准号: 10492756
• 负责人: Hyunglae Lee
• 金额: $ 26.02万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-22 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10492756
• 关键词: Address; Adherence; Algorithms; Ankle; Ankle Injuries; Atrophic; Behavioral; Behavioral Sciences; Benchmarking; Biomechanics; Chronic; Clinic; Clinical; Clinical Trials; Data; Development; Devices; Effectiveness; Engineering; Ensure; Evaluation; Feedback; Goals; Health; Individual; Injury; Instruction; Intuition; Lead; Long-Term Effects; Lower Extremity; Mechanics; Mind; Mission; Modeling; Motion; Muscle; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Nonlinear Dynamics; Observational Study; Patients; Performance; Persons; Physical activity; Prevention; Prevention strategy; Public Health; Quality of life; Recommendation; Recording of previous events; Recurrence; Research; Risk; Shoes; Sports; Sprain; System; Systems Development; Time; base; behavioral adherence; biomechanical model; clinically relevant; clinically significant; computerized data processing; design; disability; experience; follow-up; foot; human-in-the-loop; improved; injury prevention; innovation; intelligent algorithm; intervention effect; machine learning algorithm; mobile application; musculoskeletal injury; novel strategies; patient oriented; prediction algorithm; preservation; prevent; risk prediction; sensor; soft tissue; theories; wearable sensor technology; wireless

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.

拟议的研究与公共卫生相关，并且与 NIAMS 的使命非常一致，因为它 解决了提高预防脚踝扭伤有效性的巨大需求，脚踝扭伤是最严重的问题之一 常见的肌肉骨骼损伤，可显着影响身体活动和生活质量。尽管 外部被动支撑，例如脚踝绑扎和支撑，是最广泛使用的方法 预防脚踝扭伤，长期使用会使患者过度依赖被动和持续 支撑，从而导致踝关节肌肉和软组织萎缩。此外，这种做法不仅限制 内翻-外翻运动以及背屈-跖屈运动，这反过来可能会改变自然 下肢生物力学。该项目旨在研究一种独特的智能鞋系统，使用集成 工程、计算和行为科学的科学解决方案，以克服这些限制 为有脚踝受伤风险的个人提供增强的支持。我们的具体目标是：（1）设计和 实施一个智能鞋系统，该系统集成了生物力学数据的稳健、实时估计和 具有软执行器的可穿戴传感器的活动识别，能够主动调整物体的刚度 脚踝支架； (2) 对健康个体的踝关节僵硬度和足部负荷轨迹进行量化和建模 以及有脚踝扭伤风险的人； (3) 集成损伤预测算法和 闭环反馈控制器，提供主动脚踝支撑以防止扭伤； (4) 细化 开发了用于自由生活的算法，并设计了直观的移动用户界面，提供 实时总结性伤害风险指标。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进行定制 整合于心。智能鞋系统具有临床意义，因为它可以让临床医生更好地 了解足踝力学及其与各种体育活动期间踝关节受伤风险的相关性 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 遵守踝关节损伤预防策略。系统开发成功，严谨 对其以患者和临床为中心的感知效用进行评估将为后续临床奠定基础 专门旨在调查干预措施对保留/促进踝关节的长期效果的试验 健康并增强对临床建议的行为依从性。 相关性（参见说明）： 这项研究解决了提高预防踝关节扭伤有效性的迫切需要 推出智能鞋系统，可根据需要主动支撑脚踝，而不妨碍自然 踝关节运动，并提供直观的用户界面和受伤风险指标，以促进用户遵守 临床处方。该解决方案预计将大大提高当前的效率 练习被动脚踝支撑或绑带，有助于实现促进脚踝健康的长期目标。