Predict Near Future Bed Exit for Effective Intervention to Avoid Nighttime Falls

描述（由申请人提供）：拟议的研究将确定使用非侵入性，非侵入性的连续监测生命体征和床上总运动的可行性，作为早期预警系统的输入，以预测未来的下床，或试图下床，老年人跌倒的风险。预期的系统是将自动模式识别算法应用于电子病历，以提供预测能力，从而促使及时干预，避免即将发生的急性健康事件。研究目标通过确定延长健康，活跃的生命年的方法来支持NIH老龄化研究所（NIA）的目标。老年人企图或成功下床时福尔斯跌倒的后果包括髋部骨折、软组织或头部受伤、害怕受伤、或因身体不适而跌倒。 坠落焦虑抑郁和死亡拟议中的研究旨在确定一种可靠的、非侵入性的方法来预测试图离床，目的是防止随后的福尔斯摔倒及其医疗后果。拟议的研究完全符合NIA的使命，即“支持和开展与衰老过程、与衰老相关的疾病和状况以及美国老年人的其他特殊问题和需求有关的遗传、生物、临床、行为、社会和经济研究”。“该研究使用非侵入性，非接触式传感器阵列来收集心率，呼吸率，床上的总体运动和床的出口 数据正在研究的具体技术问题是，三个监测测量值（心率、呼吸率和身体运动）中的可识别变化模式是否可用于可靠地预测未来一到三分钟时间尺度上的离床或尝试离床。这项研究的更广泛的目的是引入一种具有成本效益的非侵入性方法，减少老年人跌倒相关的伤害，从而延长晚年的健康。具体目的是证明如何使用技术可靠地预测离床或试图离床，并在发生前有足够的提前期进行干预。第一阶段的重点将是测试是否有可能在预测准确性上达到统计学显著性。如果证明具有统计学意义，第二阶段将集中精力实现实际和商业意义。这项研究的成功结果表明，在其他电子医疗报告（EMR）系统中也有类似的技术创新潜力。这些技术创新，建立在拟议的研究项目的成功成果，可能是软件应用程序，或内部或基于网络的服务。 公共卫生相关性：拟议的研究旨在应用创新技术作为一种非侵入性方法，可靠地预测老年人的离床尝试，使护理人员有时间及时适当地进行干预，以防止福尔斯。跌倒和跌倒相关伤害是老年人伤害死亡的主要原因。因此，随着人口的迅速老龄化、不断增加的医疗保健成本和有限的医疗保健资源，减少福尔斯的数量和与跌倒相关的伤害具有显著和关键的相关性， 老人

DESCRIPTION (provided by applicant): The proposed research will determine the feasibility of using non-invasive, unobtrusive continuous monitoring of vital signs and gross movement in bed as input to an early warning system to forecast future bed-exit, or attempted bed-exit, by elderly persons at risk for falling. The intended system is an application of automated pattern-recognition algorithms to an electronic medical record (EMR) in order to provide predictive capability, thus prompting timely interventions to avert impending acute health events. The research objectives support the goals of the NIH Institute on Aging (NIA) by identifying a means of extending the healthy, active years of life. The consequences of falls from attempted or successful bed exits among the elderly include hip fractures, soft tissue or head injuries, fear of falling, anxiety, depression and death. The proposed research seeks to identify a reliable, non- invasive method of predicting attempted bed exits with the goal of preventing subsequent falls and their medical consequences. The proposed research is completely aligned with the NIA's mission to "support and conduct genetic, biological, clinical, behavioral, social, and economic research related to the aging process, diseases and conditions associated with aging, and other special problems and needs of older Americans." The research uses a non-invasive, non-contact sensor array to collect heartbeat rate, respiratory rate, gross motion in bed, and bed-exit data. The specific technical question being studied is whether identifiable patterns of variations in three monitored measurements (heart rate, respiratory rate, and physical movement) can be used to reliably predict bed-exit or attempted bed-exit on a time scale of one to three minutes in the future. The broader aim of the research is to introduce a cost-effective, non-invasive method of reducing fall related injuries among the elderly, thus extending health in later years. The specific aim is to demonstrate how technology can be used to reliably predict bed-exit or attempted bed-exit with sufficient lead time to intervene prior to occurrence. The emphasis in Phase I will be testing whether it is possible to achieve statistical significance in predictive accuracy on a holdout sample. If statistical significance is demonstrated, Phase II will concentrate on achieving practical and commercial significance. A successful outcome on the proposed research suggests the potential for similar technological innovation in other electronic medical report (EMR) systems. These technical innovations, built on the successful outcome of the proposed research project, may be software applications, or in- house or web-based services. PUBLIC HEALTH RELEVANCE: The proposed research seeks to apply innovative technology as a non-invasive method of reliably forecasting bed exit attempts among the elderly to allow caregivers lead time to intervene promptly and appropriately to prevent falls. Fall and fall-relate injuries are the leading cause of injury-deaths among older adults. Therefore, with a rapidly aging population, ever-increasing healthcare costs, and limited healthcare resources, there is significant and critical relevance to reducing the number of falls, and fall-related injuries among the elderly.