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有关，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巨大需求，这是最重要的 常见的肌肉骨骼损伤会严重影响体育锻炼和生活质量。尽管 外部被动支持，例如踝关节胶带和支撑，是最广泛使用的方法 预防踝关节扭伤，他们的长期使用使患者过于依赖被动和恒定 支撑，导致踝关节肌肉和软组织萎缩。此外，这种方法不仅限制了 反转运动运动，但也背屈 - 泛反射运动，这又可能改变自然 下胎生物力学。该项目旨在使用集成的 工程，计算和行为科学的科学解决方案，以克服这些局限性和 为有踝关节受伤的人提供增强的支持。我们的具体目的是：（1）设计和 实施一个智能鞋系统，该系统集成了强大的实时估计生物力学数据和 可穿戴传感器的活性识别，具有软执行器，能够主动调整刚度 脚踝支撑； （2）在健康个体中量化和建模踝关节刚度和脚负荷轨迹 以及有脚踝扭伤风险的人； （3）整合了伤害预测算法和A 闭环反馈控制器，可提供主动脚踝支撑以防止扭伤； （4）完善 开发了自由生活和设计直观移动用户界面的算法 实时的总结伤害风险指标。我们将验证和评估拟议的智能鞋系统 通过与临床合作伙伴紧密互动，以确保系统针对最佳临床量身定制 集成考虑。智能鞋系统具有临床意义，因为它将允许临床医生更好 在各种体育活动中了解脚轴力学及其与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反馈，以促进他们的 遵守踝关节损伤策略。成功开发系统和严格 评估其患者和以诊所为中心的感知效用将为后续临床奠定基础 专门研究干预措施对保存/促进踝关节的长期影响的试验 健康并增强行为遵守临床建议。 相关性（请参阅说明）： 这项研究解决了通过 引入一个智能鞋系统，该系统可以根据需要积极支撑脚踝，而不会阻碍自然 踝关节运动并提供具有伤害风险指标的直观用户界面，以促进用户遵守 临床处方。预计该解决方案将大大提高电流的有效性 被动脚踝支撑或胶带的实践，并为促进踝关节健康的长期目标做出了贡献。