对非静止的人类的呼吸速率检测,辅助运动检测
Hsi-Chou Hsu1, Wei-Hsin Chen2, Yi-Wen Lin2
1Department of Computer and Communication, National Pingtung University, Pingtung 91201, Taiwan.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
这项研究引入了一种新的算法,用于准确的非接触式呼吸率监测. 它可以识别静止时间以尽量减少运动器件,增强睡眠呼吸暂停检测和家庭护理应用.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 遥感 遥感 遥感 遥感
背景情况:
- 无接触式呼吸率监测对于睡眠呼吸暂停检测和家庭护理至关重要.
- 身体运动显著降低了非接触式呼吸监测系统的准确性.
- 现有的方法很难有效地减轻运动工件.
研究的目的:
- 开发一种算法来检测受试者的静止状态,并选择最佳的雷达回声信号,以改善呼吸监测.
- 通过最大限度地减少由身体运动引起的错误来提高非接触式呼吸率估计的准确性.
- 为了比较拟议的算法的性能与已建立的方法,如FTT,STFT和RGB-D摄像头辅助技术.
主要方法:
- 开发一种新的算法来识别人类受试者的静止期.
- 选择雷达回声信号与最小的身体运动进行呼吸分析.
- 使用快速里叶变换 (FFT),短时间里叶变换 (STFT) 和RGB-D相机辅助方法进行比较实验分析.
主要成果:
- 拟议的算法有效地识别了静止期,减少了呼吸速率估计中的运动诱导错误.
- 与连续监控相比,优化信号选择显著提高了准确性.
- 实验结果表明,与替代方法相比,根平均平方误差 (RMSE) 的性能优越.
结论:
- 开发的算法为准确的非接触呼吸监测提供了强大的解决方案,特别是在身体运动的情况下.
- 这种方法具有显著的潜力,可以提高睡眠呼吸暂停检测和远程患者监控系统的可靠性.
- 根据主体运动仔细选择信号处理窗口是提高估计准确性的关键.
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