Using high-dimensional features for high-accuracy pulse diagnosis

DOI10.3934/mbe.2020353zbMath1471.92157OpenAlexW3091915511WikidataQ104619343 ScholiaQ104619343MaRDI QIDQ1979551

Yu-Min Wang, Ching-Han Huang, Shana Smith

Publication date: 3 September 2021

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2020353

zbMATH Keywords

principal component analysisartificial neural networkhigh-dimensional featurespulse classification

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Artificial neural networks and deep learning (68T07) Medical applications (general) (92C50)

Cites Work

• Arrhythmic pulses detection using Lempel-Ziv complexity analysis
• The wavelet transform, time-frequency localization and signal analysis
• Ten Lectures on Wavelets
• Approximate entropy as a measure of system complexity.
• The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

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