论文阅读和分析:A Robust Motion Artifact Detection Algorithm for Accurate Detection of Heart Rates

论文阅读和分析:A Robust Motion Artifact Detection Algorithm for Accurate Detection of Heart Rates from Photoplethysmographic Signals using Time-Frequency Spectral Features


主要内容:

1、提取PPG信号时频谱特征,然后使用机器学习算法SVM来判断PPG信号运动伪影部分;
2、提取特征的方式比较新颖,值得学习;


流程图:

论文阅读和分析:A Robust Motion Artifact Detection Algorithm for Accurate Detection of Heart Rates_第1张图片

提取的特征:

1、使用VFCDM将PPG信号转换到时频谱;

2、计算特征:

P n o i s e P_{noise} Pnoise:
P n o i s e = P T F S − ∑ i = 1 3 ∑ t A M i , t P_{noise}=P_{TFS}-\sum_{i=1}^{3}\sum_{t}AM_{i,t} Pnoise=PTFSi=13tAMi,t
d f F M df_{FM} dfFM:
d f F M = ∑ i = 2 3 ∑ t ∣ F M i , t − i × F M 1 , t ∣ df_{FM}=\sum_{i=2}^{3}\sum_{t}\bigl|FM_{\mathrm{i},t}-i\times FM_{1,t}\bigr| dfFM=i=23t FMi,ti×FM1,t
d f H R df_{HR} dfHR:
d f H R = ∑ t ∣ F M 1 , t − m e d i a n ( 1 P P ) ∣ df_{HR}=\sum_t\left|FM_{1,t}-\mathrm{median}\left(\frac{1}{PP}\right)\right| dfHR=t FM1,tmedian(PP1)
3、使用运动造成运动伪影,作为标签label;


参考:

A Robust Motion Artifact Detection Algorithm for Accurate Detection of Heart Rates from Photoplethysmographic Signals using Time-Frequency Spectral Features

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