Cardio-Diagnostic Assisting Computer System

The mathematical analysis and the assessment of heart rate variability (HRV) based on computer systems can assist the diagnostic process with determining the cardiac status of patients. The new cardio-diagnostic assisting computer system created uses the classic Time-Domain, Frequency-Domain, and Ti...

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Main Authors: Galya Georgieva-Tsaneva, Evgeniya Gospodinova, Mitko Gospodinov, Krasimir Cheshmedzhiev
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Diagnostics
Subjects:
Online Access:https://www.mdpi.com/2075-4418/10/5/322
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spelling doaj-8daa3094026a4197833a6b285ef8faf22020-11-25T03:32:04ZengMDPI AGDiagnostics2075-44182020-05-011032232210.3390/diagnostics10050322Cardio-Diagnostic Assisting Computer SystemGalya Georgieva-Tsaneva0Evgeniya Gospodinova1Mitko Gospodinov2Krasimir Cheshmedzhiev3Institute of Robotics, Bulgarian Academy of Science, 1113 Sofia, BulgariaInstitute of Robotics, Bulgarian Academy of Science, 1113 Sofia, BulgariaInstitute of Robotics, Bulgarian Academy of Science, 1113 Sofia, BulgariaInstitute of Robotics, Bulgarian Academy of Science, 1113 Sofia, BulgariaThe mathematical analysis and the assessment of heart rate variability (HRV) based on computer systems can assist the diagnostic process with determining the cardiac status of patients. The new cardio-diagnostic assisting computer system created uses the classic Time-Domain, Frequency-Domain, and Time-Frequency analysis indices, as well as the nonlinear methods (Poincaré plot, Recurrence plot, Hurst R/S method, Detrended Fluctuation Analysis (DFA), Multi-Fractal DFA, Approximate Entropy and Sample Entropy). To test the feasibility of the software developed, 24-hour Holter recordings of four groups of people were analysed: healthy subjects and patients with arrhythmia, heart failure and syncope. Time-Domain (SDNN < 50 ms, SDANN < 100 ms, RMSSD < 17 ms) and Frequency-Domain (the spectrum of HRV in the LF < 550 ms<sup>2</sup>, and HF < 540 ms<sup>2</sup>) parameter values decreased in the cardiovascular disease groups compared to the control group as a result of lower HRV due to decreased parasympathetic and increased sympathetic activity. The results of the nonlinear analysis showed low values of (SD1 < 56 ms, SD2 < 110 ms) at Poincaré plot (Alpha < 90 ms) at DFA in patients with diseases.Significantly reducing these parameters are markers of cardiac dysfunction. The examined groups of patients showed an increase in the parameters (DET% > 95, REC% > 38, ENTR > 3.2) at the Recurrence plot. This is evidence of a pathological change in the regulation of heart rhythm. The system created can be useful in making the diagnosis by the cardiologist and in bringing greater accuracy and objectivity to the treatment.https://www.mdpi.com/2075-4418/10/5/322computer systemheart rate variabilitycardiovascular diseasesHolter recordsarrhythmiaheart failure
collection DOAJ
language English
format Article
sources DOAJ
author Galya Georgieva-Tsaneva
Evgeniya Gospodinova
Mitko Gospodinov
Krasimir Cheshmedzhiev
spellingShingle Galya Georgieva-Tsaneva
Evgeniya Gospodinova
Mitko Gospodinov
Krasimir Cheshmedzhiev
Cardio-Diagnostic Assisting Computer System
Diagnostics
computer system
heart rate variability
cardiovascular diseases
Holter records
arrhythmia
heart failure
author_facet Galya Georgieva-Tsaneva
Evgeniya Gospodinova
Mitko Gospodinov
Krasimir Cheshmedzhiev
author_sort Galya Georgieva-Tsaneva
title Cardio-Diagnostic Assisting Computer System
title_short Cardio-Diagnostic Assisting Computer System
title_full Cardio-Diagnostic Assisting Computer System
title_fullStr Cardio-Diagnostic Assisting Computer System
title_full_unstemmed Cardio-Diagnostic Assisting Computer System
title_sort cardio-diagnostic assisting computer system
publisher MDPI AG
series Diagnostics
issn 2075-4418
publishDate 2020-05-01
description The mathematical analysis and the assessment of heart rate variability (HRV) based on computer systems can assist the diagnostic process with determining the cardiac status of patients. The new cardio-diagnostic assisting computer system created uses the classic Time-Domain, Frequency-Domain, and Time-Frequency analysis indices, as well as the nonlinear methods (Poincaré plot, Recurrence plot, Hurst R/S method, Detrended Fluctuation Analysis (DFA), Multi-Fractal DFA, Approximate Entropy and Sample Entropy). To test the feasibility of the software developed, 24-hour Holter recordings of four groups of people were analysed: healthy subjects and patients with arrhythmia, heart failure and syncope. Time-Domain (SDNN < 50 ms, SDANN < 100 ms, RMSSD < 17 ms) and Frequency-Domain (the spectrum of HRV in the LF < 550 ms<sup>2</sup>, and HF < 540 ms<sup>2</sup>) parameter values decreased in the cardiovascular disease groups compared to the control group as a result of lower HRV due to decreased parasympathetic and increased sympathetic activity. The results of the nonlinear analysis showed low values of (SD1 < 56 ms, SD2 < 110 ms) at Poincaré plot (Alpha < 90 ms) at DFA in patients with diseases.Significantly reducing these parameters are markers of cardiac dysfunction. The examined groups of patients showed an increase in the parameters (DET% > 95, REC% > 38, ENTR > 3.2) at the Recurrence plot. This is evidence of a pathological change in the regulation of heart rhythm. The system created can be useful in making the diagnosis by the cardiologist and in bringing greater accuracy and objectivity to the treatment.
topic computer system
heart rate variability
cardiovascular diseases
Holter records
arrhythmia
heart failure
url https://www.mdpi.com/2075-4418/10/5/322
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