Classification of Heart Failure Based on Phase Trajectory Complexity of Seismocardiogram
Author:
Affiliation:
1. School of Information Engineering, Wuhan University of Technology, Wuhan, China
Funder
National Natural Science Foundation Committee (NSFC) of China
Application Basic Frontier Special Project of Wuhan Science and Technology Bureau
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10336249/10299601.pdf?arnumber=10299601
Reference33 articles.
1. The Applications of K-means Clustering and Dynamic Time Warping Average in Seismocardiography Template Generation
2. Comprehensive Analysis of Cardiogenic Vibrations for Automated Detection of Atrial Fibrillation Using Smartphone Mechanocardiograms
3. Nonlinear Time Series Analysis with R
4. Seismocardiography and Machine Learning Algorithms to Assess Clinical Status of Patients with Heart Failure in Cardiopulmonary Exercise Testing
5. A clinician’s guide to understanding and critically appraising machine learning studies: a checklist for Ruling Out Bias Using Standard Tools in Machine Learning (ROBUST-ML)
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1. Heart Rate Estimation using Mobile Seismocardiogram (m-SCG);2024 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES);2024-05-03
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