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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

基本信息

批准号：
10672394
负责人：
Hyunglae Lee
金额：
$ 25.86万
依托单位：
ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
依托单位国家：
美国
项目类别：
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/10672394
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 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 Populations at Risk Prevention Prevention strategy Public Health Quality of life Recommendation Recording of previous events Recurrence Research Risk Shoes Sports Sprain System Systems Development Systems Integration Time 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

项目摘要

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，这种做法不仅限制了内翻-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。