采用PPG信号的混合无声化方法,利用变化模式分解和改进的波段值
概括
这项研究引入了一种新的混合方法,以消除光斑发电学 (PPG) 信号,有效地去除运动工件和基线漂移. 改进的技术提高了信号质量,用于准确的PPG分析.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 生理监测 生理监测
背景情况:
- 摄影光电显微镜 (PPG) 信号容易受到运动工件 (MA) 和基线漂移的影响,从而影响测量准确性.
- 这些干扰显著降低了基于PPG的健康监测的可靠性.
研究的目的:
- 为PPG信号开发一个有效的无声化算法.
- 为了消除基线漂移和高频噪声,同时保留关键信号组件 (1-10 Hz).
主要方法:
- 一种混合消噪方法,结合了变化模式分解 (VMD) 和改进的波形值函数.
- VMD将PPG信号分解为内在模式函数 (IMF),以消除基线漂移.
- 应用了增强的波形值算法来消除高频噪声.
主要成果:
- 与软值相比,混合方法显著提高了信号噪声比 (SNR) 11.47%,并将根平均平方误差 (RMSE) 降低了 26.75%.
- 与单独使用改进的值函数相比,SNR (15.54%) 和RMSE (37.43%) 得到了进一步的改进.
- 对现实PPG数据,模拟信号和MIMIC-III数据库进行了验证.
结论:
- 一个强大的PPG消噪算法有效地消除了低频基线漂移和高频噪声.
- 该方法保留了PPG信号的基本形态特征.
- 该技术为PPG分析中高级时间域特征提取和模型开发提供了基础.
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