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Discrimination of Systolic and Diastolic Dysfunctions using Multi-Layer Perceptron in Heart Rate Variability Analysis
Abstract In this study, the heart rate variability (HRV) analysis is used to distinguish patients with systolic congestive heart failure (CHF) from patients with diastolic CHF. In the analysis performed, the best accuracy performances of short-term HRV measures are compared. These measures are calcu...
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Published in: | Computers in biology and medicine 2016-09, Vol.76, p.113-119 |
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description | Abstract In this study, the heart rate variability (HRV) analysis is used to distinguish patients with systolic congestive heart failure (CHF) from patients with diastolic CHF. In the analysis performed, the best accuracy performances of short-term HRV measures are compared. These measures are calculated in four different ways with optional normalization methods of heart rate and data. The nearest neighbor and the multi-layer perceptron (MLP) are used to evaluate the performances in discriminating these two groups. The results point out that using both data and heart rate normalizations enhances the classifier performance. The maximum accuracy is obtained as 96.43% with MLP classifier. |
doi_str_mv | 10.1016/j.compbiomed.2016.06.029 |
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In the analysis performed, the best accuracy performances of short-term HRV measures are compared. These measures are calculated in four different ways with optional normalization methods of heart rate and data. The nearest neighbor and the multi-layer perceptron (MLP) are used to evaluate the performances in discriminating these two groups. The results point out that using both data and heart rate normalizations enhances the classifier performance. The maximum accuracy is obtained as 96.43% with MLP classifier.</description><identifier>ISSN: 0010-4825</identifier><identifier>EISSN: 1879-0534</identifier><identifier>DOI: 10.1016/j.compbiomed.2016.06.029</identifier><identifier>PMID: 27424172</identifier><identifier>CODEN: CBMDAW</identifier><language>eng</language><publisher>United States: Elsevier Ltd</publisher><subject>Adult ; Aged ; Algorithms ; Diabetic neuropathy ; Discrimination ; Electrocardiography, Ambulatory ; Entropy ; Female ; Heart attacks ; Heart failure ; Heart Failure - classification ; Heart Failure - physiopathology ; Heart rate ; Heart Rate - physiology ; Heart rate variability ; Humans ; Internal Medicine ; Male ; Middle Aged ; Multi-layer perceptron ; Nearest neighbor ; Neural Networks (Computer) ; Normalization ; Other ; Patients ; Short term ; Studies ; Ultrasonic imaging ; Young Adult</subject><ispartof>Computers in biology and medicine, 2016-09, Vol.76, p.113-119</ispartof><rights>Elsevier Ltd</rights><rights>2016 Elsevier Ltd</rights><rights>Copyright © 2016 Elsevier Ltd. 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classification</topic><topic>Heart Failure - physiopathology</topic><topic>Heart rate</topic><topic>Heart Rate - physiology</topic><topic>Heart rate variability</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Multi-layer perceptron</topic><topic>Nearest neighbor</topic><topic>Neural Networks (Computer)</topic><topic>Normalization</topic><topic>Other</topic><topic>Patients</topic><topic>Short term</topic><topic>Studies</topic><topic>Ultrasonic imaging</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Isler, Yalcin</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Biological Sciences</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Biochemistry Abstracts 1</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - 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subjects | Adult Aged Algorithms Diabetic neuropathy Discrimination Electrocardiography, Ambulatory Entropy Female Heart attacks Heart failure Heart Failure - classification Heart Failure - physiopathology Heart rate Heart Rate - physiology Heart rate variability Humans Internal Medicine Male Middle Aged Multi-layer perceptron Nearest neighbor Neural Networks (Computer) Normalization Other Patients Short term Studies Ultrasonic imaging Young Adult |
title | Discrimination of Systolic and Diastolic Dysfunctions using Multi-Layer Perceptron in Heart Rate Variability Analysis |
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