Technology to Automatically Detect Falls and Assess Fall Risk in Senior Housing

描述（由申请人提供）：每年每三个65岁或以上的人中就有一个跌倒，这使得跌倒成为老年人受伤和因创伤住院的最常见原因，也是受伤导致死亡的主要原因（CDC, 2006）。研究人员研究了跌倒、跌倒风险评估和预防跌倒的干预措施。然而，到目前为止，他们的方法要求研究人员或临床医生完成跌倒风险的多因素评估，研究对象保持跌倒记录，佩戴测量位置变化的设备，以指示跌倒或激活需要帮助的警报。在我们目前工作的基础上，我们建议验证和部署一种创新的技术方法，该方法可以自动检测何时发生跌倒或何时跌倒的风险正在增加。受试者不需要按按钮、拉绳子或佩戴任何设备。这种在家中使用传感器的新型“被动”方法可以彻底改变检测和预防跌倒以及测量跌倒风险的方法。通过早期检测跌倒或增加跌倒风险，这项新技术可以作为老年人、家庭成员或医疗保健提供者改善身体功能或更好地管理导致跌倒的疾病的触发器。通过在任何私人住宅或公寓、老年人中心、教堂或零售商店部署新的传感器系统，本研究的产品可以改善对跌倒风险措施的获取。在这样的设置中，人们可以去一个可访问的区域来执行由本应用中开发的传感器网络测量的引导运动。在短短几分钟内，一个人就会有一个可靠的跌倒风险指示器来警告增加的跌倒风险。在老年人住房、长期护理机构、私人社区住房以及有重大跌倒风险的急性护理机构中，检测跌倒的自动传感系统具有重大潜力。经过实验室验证，由训练有素的戏剧特技演员表演567次跌倒，我们将在10个独立生活环境的老年人公寓中部署原型传感系统，进行为期两年的数据收集，以完成验证和现场测试（同样使用特技演员表演的960次跌倒）。该应用程序不仅集成了卫生保健科学学科（护理，物理治疗，社会工作，医学）的专业人才和观点，而且还集成了电气和计算机工程，计算机科学和信息学。该应用程序将对AHRQ和可能的创新和新兴感兴趣

DESCRIPTION (provided by applicant): One in every three people age 65 or older falls each year, making falls the most common cause of injuries and hospitalizations for trauma in older adults and the leading cause of death due to injury (CDC, 2006). Researchers have studied falls, fall risk assessment, and interventions to prevent falls. However, to date, their methods require that research staff or clinicians complete multi-factorial assessments of fall risk and that research subjects maintain logs of falls, wear devices that measure changes in positions that could indicate a fall or activate an alarm that they need assistance. Building on our current work, we propose to validate and deploy an innovative technological approach that automatically detects when falls have occurred or when the risk of falls is increasing. Subjects will not have to press buttons, pull cords or wear any devices. This new "passive" approach using sensors in the home could revolutionize detecting and preventing falls as well as measuring fall risk. By detecting falls or increasing fall risk early, this new technology can act as a trigger for elders, family members, or health care providers to improve physical function or better manage illnesses that are precipitating falls. The products of this study can improve access to fall risk measures by deploying the new sensor system in any private house or apartment as well as senior centers, churches, or retail stores. In such settings, persons could go to an accessible area to perform the guided motions to be measured by the sensor network developed in this application. In just a few minutes, a person would have a reliable fall risk indicator to alert increasing fall risk. An automatic sensing system to detect falls has major potential in senior housing, long-term care settings, private community housing as well in acute care settings where falls are a major risk. After laboratory validation using 567 falls performed by trained theater stunt actors, we will deploy the prototype sensing system for two years of data collection in ten apartments of elders in an independent living setting to complete validation and field testing (again using 960 falls performed by stunt actors). This application integrates the specialized talents and perspectives of not only health care scientific disciplines (nursing, physical therapy, social work, medicine) but also electrical and computer engineering, computer science, and informatics. This application will be of interest to AHRQ and likely the Innovations and Emerging Areas Portfolio that "will foster and nurture ideas and projects that have potential to lead to highly innovative solutions that may lead to significant advances in healthcare practice..."