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 跌倒是老年人致命和非致命伤害的主要原因（65岁以上）。由于下降而受伤 每年280万次紧急访问，跌倒的25％导致非常严重的伤害（例如骨折或创伤性 脑损伤）。通过这种多样性补充，对老化研究感兴趣的工程师Monroe Kennedy博士， 寻求获得Geroscience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 为了开发可穿戴的智能带装置，可以提醒佩戴者跌倒并有可能防止跌倒的风险。 结合了强大的培训计划，拟议的活动将使肯尼迪博士准备成为领导者 老年医学研究，并为衰老研究领域做出了影响力的贡献。 AIM 1将是与老年人一起在可穿戴智能设备（例如样式和）上进行焦点小组 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的SmartBelt设备 以缓慢而轻快的步伐在各种表面上行走。数据将用于训练瀑布预防模型 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 佩戴者的潜在步行轨迹和不平衡的轨迹，如果风险 跌倒是可能的。通过防止跌落首先发生，该提议的设备具有潜力 大大增加了整体福祉，长期健康和老年人的独立性以及成本 与医院探访和照料有关。