扩展:无插件设备的室内跟踪:无插件设备的室内跟踪
1Electrical and Computer Engineering Department, Stony Brook University, Stony Brook, 11794, USA. zongxing.xie@stonybrook.edu.
Scientific reports
|February 5, 2024
概括
SCALING为健康监测提供了简单,无设备的室内跟踪. 它的自我校准系统需要最小的用户努力,使家庭健康评估更容易获得.
科学领域:
- 计算机科学 计算机科学
- 无处不在的计算 无处不在的计算
- 医疗信息学 医疗信息学
背景情况:
- 在家中持续监测日常轨迹有助于评估健康状况,特别是对于阿尔茨海默氏症和痴呆症等疾病.
- 无设备的室内定位和跟踪非常适合隐蔽的健康监测,消除了可穿戴设备的需求.
- 以前的本地化方法需要广泛的手动传感器校准,限制了可扩展性和用户可访问性.
研究的目的:
- 推出SCALING,这是一款设计为非专家用户轻松设置的插入式室内轨迹监测系统.
- 通过自校准雷达技术实现可扩展的,无设备的,持续的家庭健康监测.
- 为了减少通常在室内定位系统中进行传感器校准所需的大量手工工作和专业知识.
主要方法:
- SCALING采用了一种自我校准算法,该算法根据距离测量到走短循环轨迹的用户的距离测量估计了传感器位置.
- 该系统利用放置在墙上的雷达节点,只需要一分钟的用户步行进行初始校准.
- 评估涉及模拟和两个测试台 (实验室和家庭) 具有不同的配置.
主要成果:
- 在自校准和跟踪方面,SCALING在80百分点的误差下表现出相对近似多维缩放 (MDS) 的性能优越,分别为3.5米和1.6米.
- 与使用预校准传感器位置的经典多边化相比,该系统的性能降低仅为1%.
- 蒙特卡洛实验提供了有关传感器放置影响和实际部署指南的见解.
结论:
- SCALING显著降低了室内轨迹监控的设置负担,使其可用于广泛的家庭使用.
- 该系统提供了一种实用且可扩展的解决方案,用于持续的,无设备的健康监测,支持神经疾病的早期检测和管理.
- 自校准方法使室内定位技术民主化,使非专家能够部署和使用复杂的健康监测系统.
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