A machine learning method correlating pulse pressure wave data with pregnancy

Jianhong Chen, Huang Huang, Wenrui Hao, Jinchao Xu

Research output: Contribution to journalArticle

Abstract

Pulse feeling, representing the tactile arterial palpation of the heartbeat, has been widely used in traditional Chinese medicine (TCM) to diagnose various diseases. The quantitative relationship between the pulse wave and health conditions however has not been investigated in modern medicine. In this paper, we explored the correlation between pulse pressure wave (PPW), rather than the pulse key features in TCM, and pregnancy by using deep learning technology. This computational approach shows that the accuracy of pregnancy detection by the PPW is 84% with an area under the curve (AUC) of 91%. Our study is a proof of concept of pulse diagnosis and will also motivate further sophisticated investigations on pulse waves.

Original languageEnglish (US)
Article numbere3272
JournalInternational Journal for Numerical Methods in Biomedical Engineering
Volume36
Issue number1
DOIs
StatePublished - Jan 1 2020

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Pregnancy
Chinese Traditional Medicine
Learning systems
Machine Learning
Blood Pressure
Medicine
Modern 1601-history
Palpation
Touch
Area Under Curve
Emotions
Traditional Chinese Medicine
Learning
Technology
Health
Curve

All Science Journal Classification (ASJC) codes

  • Software
  • Biomedical Engineering
  • Modeling and Simulation
  • Molecular Biology
  • Computational Theory and Mathematics
  • Applied Mathematics

Cite this

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A machine learning method correlating pulse pressure wave data with pregnancy. / Chen, Jianhong; Huang, Huang; Hao, Wenrui; Xu, Jinchao.

In: International Journal for Numerical Methods in Biomedical Engineering, Vol. 36, No. 1, e3272, 01.01.2020.

Research output: Contribution to journalArticle

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