Combined video and radar signal processing for fall detection

提高老年人和居家患者的安全性和生活质量是其动机 research.未来的家庭医疗保健系统将能够汇编他们监测的病人的信息 并且当发生诸如跌倒的紧急情况时产生可靠的警报。的常见问题 可用的家庭监视系统是频繁的假警报，这可能导致对警报的不敏感， 错过的警报目前解决这个问题的方法包括使用不同类型和位置的 传感器，信号处理方法，以提取更有用的数据，然后再作出决定， 开发各种分类方法以生成警报。 在这个项目中，我们将与Remotronic合作，以确定他们的跌倒检测解决方案的准确性， 并将其精度与基于雷达的解决方案进行比较。基于摄像头的解决方案 因为照相机是广泛可用的并且便宜。基于雷达的解决方案可以检测福尔斯 能够穿透墙壁并提取呼吸和心跳信号。这项研究的结果将是一个 提出了一种解决方案，该解决方案将以更高的准确度检测紧急事件，例如福尔斯，并区分 这些事件都是假警报

Improved safety and quality of life for elderly people and home-bound patients is the motivation for this research. Future home health care systems will be able to compile information about the patients they monitor and produce reliable alarms when an emergency situation, such as fall, occurs. A common problem with available home monitoring systems is frequent false alarms, which can result in desensitization to alarms and missed alarms. Current approaches for addressing this problem include using different types and placement of sensors, signal processing approaches to extract more useful data before making decisions, and the development of various classification methods to generate alarms. In this project, we will work with Remotronic to determine the accuracy of their fall-detection solution based on off-the-shelf cameras and to compare the accuracy against the radar based solution. A camera-based solution has advantage because cameras are widely available and inexpensive. Radar-based solutions can detect falls through walls and are capable of extracting breathing and heartbeat signals. The result of this research will be a proposal of a solution that will detect emergency events, such as falls, with higher accuracy, and differentiate these events from false alarms.