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使用低成本的CW多普勒雷达传感器进行有效的摔倒检测和摔倒后呼吸速率跟踪
Ritesh Chandra Tewari1, Sandeep Sharma2, Aurobinda Routray2
1Advanced Technology Development Centre, Indian Institute of Technology, Kharagpur, West Bengal, India.
Computers in biology and medicine
|August 12, 2023
概括
这项研究引入了一种低成本的多普勒雷达落检测系统,可以减少错误报警,并增加落后的健康监测. 精确而高效的系统实现了93.24%的摔倒检测准确度.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 现有的多普勒雷达落探测系统存在错误报警,缺乏落后健康跟踪.
- 这些局限性降低了对现实应用的准确性和整体适用性.
研究的目的:
- 开发一个具有成本效益和强大的摔倒检测系统,并集成了摔倒后的健康跟踪.
- 通过提高准确性和减少错误报警来解决当前系统的局限性.
主要方法:
- 使用3.18GHz连续波多普勒雷达传感器进行数据采集.
- 开发了一个四个阶段的等级算法,在每个阶段进行训练,以优化分类.
- 采用模块化系统架构,使用低功耗设备和传统的机器学习算法来最大限度地降低计算成本和功耗.
主要成果:
- 实现了93.24%的跌落检测准确度.
- 显示呼吸速率测量的误差为2.26%.
- 结果与当前最先进的方法具有竞争力.
结论:
- 拟议的系统有效地克服了错误警报,并使落后的健康跟踪成为可能.
- 该系统提供了一种具有成本效益,准确和强大的解决方案,用于降落检测.
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