Unsupervised learning-based non-invasive fetal ecg muti-level signal quality assessment

HIGHLIGHTS

  • who: Xintong Shi et al. from the Graduate School of Science and Technology, Keio University, Yokohama, Japan have published the research: Unsupervised Learning-Based Non-Invasive Fetal ECG Muti-Level Signal Quality Assessment, in the Journal: Bioengineering 2023, 10, 66. of /2023/
  • what: A preliminary version of this work has been reported . The main contributions of the work are as follows: (i) A novel AE-based feature for SQA is introduced. In the research , four entropy-based features are calculated :. The aim of DFA is to extract longrange correlation in non-stationary time series.
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