A dual-polarized Doppler Radar system for fall detection in an indoor environment

 描述(由申请人提供)：跌倒是老年人(OAS)受伤和死亡的主要原因，鉴于美国未来OAS数量的预测，跌倒将成为一个日益严重的公共卫生问题。需要跌倒检测和/或监视系统来增强办公自动化的信心和独立性，并促进跌倒后的快速反应。该项目将开发一种低成本的坠落检测系统，以促进在不同的室内环境中进行被动和无线的坠落检测，并且可以很容易地转化为市场产品。该系统的核心是使用双极化多普勒雷达，这是对现有雷达系统的改进，用于跌倒检测，还克服了替代方法的几个限制(例如，依赖于患者对可穿戴传感器的遵从性，基于视频的系统的隐私问题)。这个项目涉及三个目标。在目标1中，我们将通过设计一种适用于实际室内使用的双极化天线来开发该系统，该天线使用圆极化、短桩加载的螺旋天线发射和双线极化接收天线。设计的天线系统的性能将经过评估，然后集成到商业软件定义的无线电中，并随后进行测试，以确定信号检测范围和角度覆盖范围，并确定最佳安装位置。在目标2中，将获得模拟跌倒和每日活动的实验数据 生活在一个庞大而多样的人类参与者样本中。利用这些数据，在目标3中，我们将开发和评估一种新的跌倒检测算法。该算法将使用多种分类技术和决策融合方法，以受益于所提出的雷达系统提供的丰富信息。目前的项目在使用双极化方面是新颖的，目标是利用即将到来的频谱共享频段。它的创新之处在于，在跌倒检测算法中利用了极化分集，这有望减少错误警报，并强调严重跌倒和非严重跌倒的区分。将开发一个广泛的实验数据库，包括比以往许多研究更广泛的活动和事件(包括滑倒/绊倒引起的跌倒)，以及更广泛的个体间多样性的表现。通过设计，建议的系统有望成为一个有效的、低成本的普适性室内跌倒检测系统，具有较小的外形尺寸，并且与其他跌倒检测方法相比，提供更少的侵入性、更丰富和更可靠的信息(例如，低错误警报率)。

 DESCRIPTION (provided by applicant): Falls are a leading cause of injuries and deaths among older adults (OAs), and will be an increasing public health concern given projections of future increases in the number of OAs in the US. Fall detection and/or surveillance systems are needed to enhance an OA's confidence and independence, and to facilitate rapid post-fall responses. This project will develop a low-cost fall detection system, to facilitate passive and wireless fall detection in diverse indoor environments, and which can be easily translated into a market product. Central to this system is the use of dual-polarized Doppler radar, an enhancement over existing radar systems for fall detection, and which also overcomes several limitations of alternative approaches (e.g., dependency on patient compliance with wearable sensors, privacy concerns with video-based systems). This project involves three Aims. In Aim #1, we will develop the system by designing a dual-polarized antenna for application to realistic indoor use, using a circularly-polarized, stub-loaded helix antenna for transmitting and a dual-linearly-polarized receiving antenna. Performance of the designed antenna system will be assessed, then integrated into a commercial software-defined radio, and subsequently tested to characterize signal detection range and angular coverage and to determine the best installation location. In Aim #2, experimental data will be obtained for simulated falls and activities of daily living, from among a large and diverse sample of human participants. Using these data, in Aim #3 we will develop and evaluate a new fall detection algorithm. This algorithm will employ multiple classification technologies and decision fusion methods to benefit from the rich information provided by the proposed radar system. The current project is novel in the use of dual-polarization, and is targeted to harness the upcoming spectrum- sharing band. It is innovative in taking advantage of polarization diversity in a fall detection algorithm, which is expected to decrease false alarms, and also in emphasizing the discrimination of critical vs. non-critical falls. An extensive experimental database will be developed, including a wider range of activities and events (including slip/trip induced falls), and broader representation of inter-individual diversity, than in many prior studies. By design, the proposed system is expected be an effective, low-cost pervasive indoor fall detection system, with a small form factor, and that provides less intrusive, richer, and more reliable information (e.g. low false alarm rate) than alternative approaches for fall detection.