毫米波RM:一种基于毫米波雷达的呼吸监测和模式分类系统
Zhanjun Hao1,2, Yue Wang1, Fenfang Li1
1College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China.
Sensors (Basel, Switzerland)
|July 13, 2024
概括
这项研究使用毫米波 (mmWave) 雷达进行非接触式呼吸监测. 该系统准确地检测到各种呼吸模式,有助于早期发现心肺问题.
科学领域:
- 生物医学工程 生物医学工程
- 医疗器械 医疗器械
- 信号处理 信号处理
背景情况:
- 异常的呼吸模式可能意味着严重的心肺疾病.
- 早期发现呼吸系统异常对于预防疾病进展至关重要.
- 需要非接触式监测方法来进行持续和不引人注目的患者评估.
研究的目的:
- 开发和验证使用毫米波 (mmWave) 雷达的非接触呼吸系统监测系统.
- 准确地分类不同的呼吸模式,包括正常,缓慢/深,快速和脑膜炎呼吸.
- 为了减轻噪声干扰,在日常环境中可靠地检测呼吸信号.
主要方法:
- 使用77 GHz频率调制连续波 (FMCW) 毫米波雷达进行非接触式信号采集.
- 应用信号叠加和圆过 (0.1-0.5 Hz),以减少静态噪声.
- 使用面向梯度 (HOG) 功能提取的基底图形与K-最近邻居 (KNN),卷积神经网络 (CNN) 和G-SVM用于呼吸模式分类.
主要成果:
- 在分类四种不同的呼吸模式方面取得了很高的准确性.
- 证明了毫米波雷达在捕获微妙呼吸信号方面的有效性.
- 成功过环境噪声,以提高信号清晰度和波形精度.
结论:
- 毫米波雷达系统为非接触式呼吸监测提供了有效的解决方案.
- 开发的分类算法准确地识别出各种呼吸模式.
- 这项技术支持加强日常医疗监测和早期疾病检测.
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