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.

摘要 福尔斯是老年人（65岁以上）致命和非致命伤害的主要原因。由于跌倒造成的伤害 2.8每年有100万人次的急诊就诊，25%的福尔斯跌倒导致非常严重的伤害（如骨折或创伤性 脑损伤）。通过这种多样性的补充，门罗肯尼迪博士，一个对衰老研究感兴趣的工程师， 寻求老年科学方面的培训和指导。作为这种多样性补充的一部分，肯尼迪博士建议 开发一种可穿戴的智能腰带设备，该设备可以提醒穿戴者有跌倒的风险，并可能防止福尔斯。 结合一个强大的培训计划，拟议的活动将准备肯尼迪博士成为一个领导者， 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将是对老年人进行可穿戴智能带设备的焦点小组，如风格和 令人担心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SmartBelt设备，同时 以缓慢和轻快的步伐在各种表面上行走。数据将用于训练福尔斯预防模型 利用机器学习方法。最终目标是让模型能够通过预测来计算跌倒风险 潜在的步行轨迹和不平衡，并通过振动触觉响应警告穿戴者，如果风险 下降是可能的。通过首先防止发生福尔斯，所提出的装置具有潜力 大大提高老年人的整体福祉、长期健康和独立性以及成本 与医院访问和住院有关。