Stanford Aging & Ethnogeriatrics Transdisciplinary Collaborative Center (SAGE)

斯坦福老龄化

• 批准号: 10319307
• 负责人: Victor Henderson
• 金额: $ 3.53万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10319307
• 关键词: Age; Aging; Data; Devices; Elderly; Emergency Situation; Engineering; Ensure; Fall prevention; Focus Groups; Fracture; Geriatrics; Geroscience; Goals; Health; Hospitals; Injury; Mentors; Modeling; Personal Satisfaction; Quality of life; Research; Surface; Technology; Testing; Training; Traumatic Brain Injury; Visit; Visual; Walking; caregiving; cost; fall risk; falls; improved; interest; machine learning method; prevent; response; sensor

ABSTRACT Falls are the leading cause of fatal and non-fatal injuries in older adults (ages 65+). Injuries due to falling result in 2.8 million emergency visits annually, and 25% of falls result in very serious injuries (such as fractures or traumatic brain injury). Through this diversity supplement, Dr. Monroe Kennedy, an engineer interested in aging research, seeks to get training and mentoring in geroscience. As part of this diversity supplement, Dr. Kennedy, proposes to develop a wearable smartbelt device that can alert the wearer to risk of falling and potentially prevent falls. Combined with a robust training plan, the proposed activities will prepare Dr. Kennedy to become a leader in geriatrics research and make impactful contributions to the field of aging research. Aim 1 will be to conduct focus groups with older adults on the wearable smartbelt device, such as style and comfort. Aim 2 will test the wearable smartbelt device by collecting visual and sensor data from older adults while walking on various surfaces at slow and brisk paces. The data will be used to train the falls prevention model utilizing machine learning methods. The ultimate goal is for the model to be able to calculate fall risk by predicting potential walking trajectories of the wearer and imbalance and alert the wearer via vibrotactile response if the risk of falling is probable. By preventing falls from occurring in the first place, the proposed device has the potential to greatly increase the overall well-being, long-term health, and independence of older adults as well as costs associated with hospital visits and caregiving.

抽象的 跌倒是老年人（65 岁以上）致命和非致命伤害的主要原因。跌倒导致受伤 每年有 280 万次紧急就诊，其中 25% 的跌倒会导致非常严重的伤害（例如骨折或外伤） 脑损伤）。通过这种多样性补充，对衰老研究感兴趣的工程师 Monroe Kennedy 博士， 寻求获得老年科学方面的培训和指导。作为多样性补充的一部分，肯尼迪博士建议 开发一种可穿戴智能腰带设备，可以提醒佩戴者跌倒风险并可能防止跌倒。 结合强大的培训计划，拟议的活动将使肯尼迪博士成为领导者 老年医学研究并为老龄化研究领域做出有影响力的贡献。 目标 1 是就可穿戴智能腰带设备与老年人进行焦点小组讨论，例如风格和 舒适。 Aim 2 将通过收集老年人的视觉和传感器数据来测试可穿戴智能腰带设备 以缓慢和快速的步伐在各种表面上行走。该数据将用于训练跌倒预防模型 利用机器学习方法。最终目标是使模型能够通过预测来计算跌倒风险 佩戴者的潜在行走轨迹和不平衡，并通过振动触觉响应提醒佩戴者如果存在风险 跌倒是有可能的。通过从一开始就防止跌倒发生，所提出的设备具有潜力 大大提高老年人的整体福祉、长期健康和独立性以及成本 与医院就诊和护理有关。