Mitigating Injurious Falls in Older Adults Through Non-Injurious Fall and Gait Analysis From Floor Vibrations

通过非伤害性跌倒和地板振动的步态分析来减轻老年人的伤害性跌倒

• 批准号: 10383468
• 负责人: Stacy Lynne Fritz
• 金额: $ 74.02万
• 依托单位: ADVANCED SMART SYSTEMS/EVALUATION TECHNO
• 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 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10383468
• 关键词: Accelerometer; Adopted; Adoption; Adult; Age; Alzheimer' s disease related dementia; Area; Assisted Living Facilities; Back; Beds; Cause of Death; Communities; Data; Detection; Devices; Disasters; Discipline of Nursing; Effectiveness; Elderly; Financial Hardship; Fire - disasters; Floor; Future; Gait; Gait speed; Generations; Goals; Hand; Health; Health Status; Health care facility; Healthcare; Home; Hospitals; Impaired cognition; Individual; Industry Standard; Injury; Insurance; Insurance Carriers; Intelligence; Left; Legal; Legal patent; Letters; Lutheran Church; Measurement; Measures; Medical; Medical center; Methods; Modeling; Monitor; Motion; Nursing Homes; Operating System; Patient Monitoring; Patients; Patients' Rooms; Penetration; Personal Satisfaction; Persons; Phase; Physicians' Offices; Preventive healthcare; Privacy; Property; Quality of life; Recording of previous events; Reporting; Risk; Risk Assessment; Savings; South Carolina; System; Technology; Time; TimeLine; United States Department of Veterans Affairs; Universities; Ursidae Family; Work; aging in place; base; care providers; combat; cost; design; detection platform; experience; fall injury; fall risk; falls; feature detection; gait examination; human old age (65+); improved; injury-related death; innovation; innovative technologies; insight; operation; predictive modeling; pressure; prisma; sensor; tool; vibration; wearable device; wearable sensor technology

Project Summary and Abstract Falls are the leading cause of death due to injury. Falls are so common that 30% of community dwelling older adults, and 50% of residents in Care Facilities will experience a fall in the coming year. The risk of falling substantially increases for those having Alzheimer’s disease and related dementias. The financial burden is significant with fall-related costs being $50 billion. Care Facilities, who are often liable for the well-being of their patients, bear a substantial portion of the cost. A fall can cost $10,484 per case for Care Facilities. Commercially available fall detection systems operate via wearable pendant-based devices that patients press after experiencing a fall. Newer generations of these systems also incorporate accelerometers that are reportedly able to detect falls. These systems are patient-dependent, meaning that a patient must be wearing the pendant for it to work which older adults, particularly those with cognitive impairments, often do not. Furthermore, the patient has to be cognizant to press the button to call for aid if the pendant does not activate during a fall. This is unlikely to occur as even when people are not cognitively impaired, they will only activate the system 20% of the time. There is a clear need for an automated, patient-independent fall detection system to fill the gaps left by current approaches. Better yet would be a system that can detect non-injurious falls or changes in gait parameters, both of which are predictors of oncoming injurious falls. ASSET, in partnership with the University of South Carolina, has developed a patented, floor vibration monitoring system that can detect falls and collect gait information whilst being patient independent. The innovative product has the ability to firmly place control of liability back into the hands of Care Facilities much like what a fire alarm does for property damage from fires, and potentially saving ~$2.2 billion in fall-related costs with just 5% market adoption. During Phase II our overall goals are two-fold, first to further develop a system that does not rely on the patient to operate, overcoming the limitation of wearable systems and can additionally capture falls that are a predictor of oncoming injurious falls. We will monitor common areas with our vibration sensor system in places where Care Facility staff report the majority of falls occur. To accomplish the methods, we will use the Care Facilities’ common area video camera system to corroborate sensor fall activations are actual falls. Second, we will use the same passive system technology to explore gait measurement as an additional indicator of an oncoming health changes such as a fall. We will use gait parameter measuring technology in a Care Facility medical office for regular vital monitoring. We will use gait measurements with Facility fall reports to explore the effectiveness of our predictive fall risk model against industry-standard fall risk assessments. Future directions will include ASSET launching Beta trials of the product among Care Facilities for final refinement of the product before full release to the public.

项目概要和摘要 福尔斯是因伤致死的主要原因。福尔斯是如此的普遍， 成年人和50%的护理机构居民将在未来一年经历下降。下跌的风险 对于那些患有阿尔茨海默病和相关痴呆症的人来说，财政负担 与秋季相关的成本为500亿美元。护理机构通常对他们的福祉负责 患者承担了很大一部分费用。每例跌倒的护理设施费用为10,484美元。 市售的跌倒检测系统经由患者按压的可穿戴的基于吊坠的设备来操作。 在经历了一次跌倒之后。新一代的这些系统还包括加速度计， 据说能探测到福尔斯。这些系统依赖于患者，这意味着患者必须佩戴 吊坠，它的工作，老年人，特别是那些有认知障碍，往往没有。 此外，患者必须意识到，如果吊坠未激活，则按下按钮以呼叫援助 在坠落过程中这是不太可能发生的，因为即使人们没有认知障碍，他们也只会激活 系统20%的时间。 显然需要一种自动化的、独立于患者的跌倒检测系统来填补当前跌倒检测系统所留下的空白。 接近。更好的是一个可以检测非伤害性福尔斯或步态参数变化的系统， 这两者都是即将到来的有害福尔斯坠落的预测器。ASSET与南方大学合作 卡罗莱纳，开发了一种专利，地板振动监测系统，可以检测福尔斯和收集步态 信息，同时患者独立。创新产品有能力牢牢控制 责任回到护理机构手中，就像火灾报警器对火灾造成的财产损失一样， 仅5%的市场采用率就可能节省约22亿美元的秋季相关成本。 在第二阶段，我们的总体目标是双重的，首先是进一步开发一个不依赖于病人的系统 克服了可穿戴系统的限制，并且还可以捕获作为预测器的福尔斯 即将到来的伤害性福尔斯。我们将使用振动传感器系统监控公共区域， 护理机构的工作人员报告说，大多数福尔斯跌倒。为了实现这些方法，我们将使用护理机构的 公共区域视频摄像机系统来证实传感器跌倒激活是实际的福尔斯。第二，我们将使用 同样的被动系统技术，探索步态测量作为一个额外的指标， 健康状况发生变化，如跌倒。我们将在护理机构医疗中使用步态参数测量技术 定期生命监测办公室。我们将使用步态测量与设施跌倒报告，以探讨 我们的预测性跌倒风险模型对行业标准跌倒风险评估的有效性。未来方向 将包括ASSET在护理机构中启动产品的Beta测试，以最终完善产品 在完全释放给公众之前。