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Higher Order Dynamic Mode Decomposition: from Fluid Dynamics to Heart Disease Analysis [article]

Nourelhouda Groun, Maria Villalba-Orero, Enrique Lara-Pezzi, Eusebio Valero, Jesus Garicano-Mena, Soledad Le Clainche
2022
In this work, we study in detail the performance of Higher Order Dynamic Mode Decomposition (HODMD) technique when applied to echocardiography images.  ...  HODMD is a data-driven method generally used in fluid dynamics and in the analysis of complex non-linear dynamical systems modeling several complex industrial applications.  ...  Figure 1 : Schematic diagram for the higher order dynamic mode decomposition (HODMD) analysis pipeline.  ... 
doi:10.48550/arxiv.2201.03030 fatcat:zczkdz2fb5cfbdrdtuilg7n2ee

Analysis of ECG Signals by Dynamic Mode Decomposition

Honorine Niyigena Ingabire, Kangjia Wu, Joan Toluwani Amos, Sixuan He, Xiaohang Peng, Wenan Wang, Min Li, Jinying Chen, Yukun Feng, Nini Rao, Peng Ren
2021 IEEE journal of biomedical and health informatics  
Dynamic mode decomposition (DMD) was first used to decompose ECG signals into dynamic modes (DMs) which can be regarded as ECG subsystems.  ...  We used seven different cardiac pathologies (myocardial infarction, cardiomyopathy, bundle branch block, dysrhythmia, hypertrophy, myocarditis, and valvular heart disease) to illustrate our method.  ...  Content may change prior to final publication.  ... 
doi:10.1109/jbhi.2021.3130275 pmid:34818197 fatcat:v3qx6ky4dff7xdelx7fnvrpqhy

Spectral Decomposition and Sound Source Localization of Highly Disturbed Flow through a Severe Arterial Stenosis

Fardin Khalili, Peshala T Gamage, Amirtahà Taebi, Mark E Johnson, Randal B Roberts, John Mitchel
2021 Bioengineering  
Additionally, the visualization of the most energetic proper orthogonal decomposition (POD) mode and spectral decomposition of the flow indicated that the break frequencies ranged from 80 to 220 Hz and  ...  In this study, a multifaceted comprehensive approach involving advanced computational fluid dynamics combined with signal processing techniques was exploited to investigate the highly turbulent fluctuating  ...  and run the equipment needed for the experiments, Jordan Waldheim from Dantec Dynamics A/S helped us to perform the LDA measurements, and Andy Bussey supported us by participating in our discussion to  ... 
doi:10.3390/bioengineering8030034 pmid:33806695 pmcid:PMC8000318 fatcat:bcnjn2b6p5dzradytfssb6m3oi

Unsupervised EHR-based Phenotyping via Matrix and Tensor Decompositions [article]

Florian Becker, Age K. Smilde, Evrim Acar
2022 arXiv   pre-print
Discovering (novel) phenotypes has the potential to be of prognostic and therapeutic value.  ...  Especially extracting temporal phenotypes from longitudinal EHR has received much attention in recent years.  ...  Tensor Decompositions Higher-order tensors (or multi-way arrays) are higher-order extensions of data matrices. We use X ∈ R I1,...,IK to denote a tensor of order K.  ... 
arXiv:2209.00322v1 fatcat:xqziwv3ifjeo7njle5xo4zfocy

Exploring the Use of Proper Orthogonal Decomposition for Enhancing Blood Flow Images Via Computational Fluid Dynamics [chapter]

Robert McGregor, Dominik Szczerba, Martin von Siebenthal, Krishnamurthy Muralidhar, Gábor Székely
2008 Lecture Notes in Computer Science  
We propose a novel approach to integrate computational fluid dynamics with measurement data to overcome this difficulty.  ...  By performing a proper orthogonal decomposition of simulated blood flow patterns for a given vascular location with various anatomical configurations it is possible to obtain a basis model for flow reconstruction  ...  POD, known in other fields as Principal Component Analysis or Karhunen-Loève Transform is a widely used tool in Fluid Dynamics.  ... 
doi:10.1007/978-3-540-85990-1_94 fatcat:cncot6px3jbj5nnodq2634odia

De-Noising Corrupted ECG Signals By Empirical Mode Decomposition (EMD) With Application of Higher Order Statistics (HOS)

2013 IOSR Journal of Applied Physics  
In this paper, an algorithm is developed to de-noise ECG signals based on Empirical Mode Decomposition (EMD) with application of Higher Order Statistics (HOS).  ...  The electrocardiogram (ECG) signals which are extensively used for heart disease diagnosis and patient monitoring are usually corrupted with various sources of noise.  ...  In this paper, an algorithm has been developed to de-noise ECG signal based on Empirical Mode Decomposition (EMD) along with application of Higher Order Statistics (HOS).  ... 
doi:10.9790/4861-0414752 fatcat:frcrvy72rbayhkheubmcy4tvtq

Analyzing Transient Turbulence in a Stenosed Carotid Artery by Proper Orthogonal Decomposition

Leopold Grinberg, Alexander Yakhot, George Em Karniadakis
2009 Annals of Biomedical Engineering  
Time-and space-window proper orthogonal decomposition (POD) was applied to quantify the different flow regimes in the occluded artery.  ...  The geometrical model was reconstructed from MRI images, and in vivo velocity measurements were incorporated in the simulations to provide inlet and outlet boundary conditions.  ...  According to the American Heart Association, the carotid disease is the major risk factor for ischemic stroke, caused by detachment of the plaque, which may clot vital brain vessels.  ... 
doi:10.1007/s10439-009-9769-z pmid:19669884 fatcat:j6zpsgooyfhj5nbjiykjzhnqoy

A Novel Data-Driven Method for the Analysis and Reconstruction of Cardiac Cine MRI [article]

Nourelhouda Groun, Maria Villalba-Orero, Enrique Lara-Pezzi, Eusebio Valero, Jesus Garicano-Mena, Soledad Le Clainche
2022 arXiv   pre-print
This work considers the application of the higher order dynamic mode decomposition (HODMD) method to a set of MR images of a heart, with the ultimate goal of identifying the main patterns and frequencies  ...  This algorithm is applied (i) to reconstruct corrupted or missing images, and (ii) to build a reduced order model of the heart dynamics.  ...  Higher Order Dynamic Mode Decomposition Higher order dynamic mode decomposition (HODMD) is an extension of the well known method dynamic mode decomposition (DMD) [23] , which was first introduced the  ... 
arXiv:2205.12097v1 fatcat:lnrbr2eqjndgvfyxa27xn2bdym

Data-driven cardiovascular flow modeling: examples and opportunities [article]

Amirhossein Arzani, Scott T. M. Dawson
2021 arXiv   pre-print
modeling for cardiovascular flows, including the dynamic mode decomposition (DMD), and the sparse identification of nonlinear dynamics (SINDy).  ...  In particular, we discuss principal component analysis (PCA), robust PCA, compressed sensing, the Kalman filter for data assimilation, low-rank data recovery, and several additional methods for reduced-order  ...  Data Availability The codes and data used to generate the results in the manuscript will be made publicly available after peer-review. p. 30  ... 
arXiv:2010.00131v2 fatcat:kgjzb4mup5amjdnfipoekthm4q

Detecting scaling in the period dynamics of multimodal signals: Application to Parkinsonian tremor

Nir Sapir, Roman Karasik, Shlomo Havlin, Ely Simon, Jeffrey M. Hausdorff
2003 Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics  
In contrast, when the method is applied to tremor records from patients with Parkinson's disease, the first two modes of oscillations yield different scaling patterns, suggesting that these modes may not  ...  We propose a method to extract the correlation ͑scaling͒ properties in the period dynamics of multimodal oscillations, in order to distinguish between a nonlinear oscillation and a superposition of individual  ...  Therefore, in order to enable scaling analysis of tremor, specifically, and signals consisting of several modes, more generally, it is essential to develop a new method for identifying the period dynamics  ... 
doi:10.1103/physreve.67.031903 pmid:12689097 fatcat:thnx36ed4vbvfllowukmawlxj4

RV functional imaging: 3-D echo-derived dynamic geometry and flow field simulations

Ares D. Pasipoularides, Ming Shu, Michael S. Womack, Ashish Shah, Olaf von Ramm, Donald D. Glower
2003 American Journal of Physiology. Heart and Circulatory Physiology  
image analysis; ventricular function; cardiac fluid dynamics; right ventricle; heart chamber volume  ...  Finally, the RV endocardial border motion information is used for mesh generation on a computational fluid dynamics solver to simulate development of the early RV diastolic inflow field.  ...  The final phase, computational fluid dynamics (CFD) simulation, applies boundary conditions from the endocardial border motion data to a finite element method (FEM)-based fluid dynamics software.  ... 
doi:10.1152/ajpheart.00577.2002 pmid:12388220 pmcid:PMC5789451 fatcat:d5s5eec7u5bpjbskxstrgetx74

Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows [article]

Hamidreza Eivazi, Soledad Le Clainche, Sergio Hoyas, Ricardo Vinuesa
2021 arXiv   pre-print
We propose a deep probabilistic-neural-network architecture for learning a minimal and near-orthogonal set of non-linear modes from high-fidelity turbulent-flow-field data useful for flow analysis, reduced-order  ...  Moreover, we introduce an algorithm for ordering VAE-based modes with respect to their contribution to the reconstruction.  ...  Acknowledgments We acknowledgeÁlvaro Martínez for his contributions to this work. RV acknowledges the Göran Gustafsson foundation for the financial support of this research.  ... 
arXiv:2109.01514v1 fatcat:ls72smph5nechjgkgke5zyz7iq

A laboratory investigation of the flow in the left ventricle of a human heart with prosthetic, tilting-disk valves

A. Cenedese, Z. Del Prete, M. Miozzi, G. Querzoli
2005 Experiments in Fluids  
On one hand, more accurate investigation techniques gives the chance to better diagnose diseases before they become dangerous to the health of the patient.  ...  The flow was studied both kinematically, examining velocity and vorticity fields, and dynamically, evaluating turbulent and viscous shear stresses, and inertial forces exerted on fluid elements.  ...  Acknowledgements The authors wish to thank Fabiana Giorgi for her contribution in the realisation of the silicon rubber model of the ventricle and the data acquisition.  ... 
doi:10.1007/s00348-005-1006-4 fatcat:vedssrzcwrdhfhz57ump5piusq

Body Acoustics for the Non-Invasive Diagnosis of Medical Conditions

Jadyn Cook, Muneebah Umar, Fardin Khalili, Amirtahà Taebi
2022 Bioengineering  
In the past few decades, many non-invasive monitoring methods have been developed based on body acoustics to investigate a wide range of medical conditions, including cardiovascular diseases, respiratory  ...  problems, nervous system disorders, and gastrointestinal tract diseases.  ...  The acoustic signals can be also decomposed into their components using methods such as ensemble empirical mode decomposition and variational mode decomposition [16, 17] .  ... 
doi:10.3390/bioengineering9040149 pmid:35447708 pmcid:PMC9032059 fatcat:b6xrfal4trgaxjsu75pt32uevq

ADAPTIVE DATA ANALYSIS OF COMPLEX FLUCTUATIONS IN PHYSIOLOGIC TIME SERIES

C.-K. PENG, MADALENA COSTA, ARY L. GOLDBERGER
2009 Advances in Adaptive Data Analysis  
In particular, we discuss the importance of applying adaptive data analysis techniques, such as the empirical mode decomposition algorithm, to address the challenges of nonlinearity and nonstationarity  ...  We introduce a generic framework of dynamical complexity to understand and quantify fluctuations of physiologic time series.  ...  We gratefully acknowledge the support from the NIH/NIBIB and NIGMS (U01-EB008577), the NIH/NIA OAIC (P60-AG08814), the NIH/NICHD (R01-HD39838), the NIH/NINDS (R01-NS45745), the Defense Advanced Research  ... 
doi:10.1142/s1793536909000035 pmid:20041035 pmcid:PMC2798133 fatcat:mau3v2ybjjcbxgk4rpjlspd3cy
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