Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/92384
Title: Diagnostics of the arterial hypertension by means of the discriminant analysis analysis of the heart rate variability signals features combinations
Authors: Kublanov, V.
Dolganov, A.
Kazakov, Y.
Issue Date: 2017
Publisher: SciTePress
Citation: Kublanov V. Diagnostics of the arterial hypertension by means of the discriminant analysis analysis of the heart rate variability signals features combinations / V. Kublanov, A. Dolganov, Y. Kazakov. — DOI 10.5220/0006107902910298 // BIOSIGNALS 2017 - 10th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017. — 2017. — Iss. 4. — P. 291-298.
Abstract: The paper presents investigation of the diagnostic possibilities of the arterial hypertension using linear and quadratic combinations of the heart rate variability signals features. For this study, two groups were considered: healthy volunteers and patients suffering from the arterial hypertension of the II-III degree. For the study, features of statistical, geometric, spectral, nonlinear and multifractal methods were investigated. Results of the analysis have shown that among studied combinations four feature sets (heart rate, features of the VLF frequency band and LF/HF ratio) have the highest classification accuracy – 93%. Copyright © 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
Keywords: ARTERIAL HYPERTENSION
CLASSIFICATION
DISCRIMINANT ANALYSIS
HEART RATE VARIABILITY
BIOMEDICAL ENGINEERING
BIOMIMETICS
CARDIOLOGY
DIAGNOSIS
DISCRIMINANT ANALYSIS
HEART
ARTERIAL HYPERTENSION
CLASSIFICATION ACCURACY
FEATURE SETS
HEALTHY VOLUNTEERS
HEART RATE VARIABILITY SIGNALS
HEART RATES
MULTI FRACTALS
SIGNAL PROCESSING
URI: http://elar.urfu.ru/handle/10995/92384
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85031328718
WOS ID: 000413256500039
PURE ID: 6018506
ISBN: 9789897582127
DOI: 10.5220/0006107902910298
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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