Multi-fractal detrended fluctuation half-spectrum analysis of HRV
Electrocardiogram is a comprehensive reflection of cardiac electrical activity on the surface of the body. It is of great research value to analyse ECG signals and diagnose heart diseases. Since the heartbeat process is a chaotic system, this study proposes a multi-fractal detrended fluctuation half...
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Online Access: | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.1067 |
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doaj-d11ca85089184abd8515504c0abe07712021-04-02T17:40:37ZengWileyThe Journal of Engineering2051-33052019-11-0110.1049/joe.2019.1067JOE.2019.1067Multi-fractal detrended fluctuation half-spectrum analysis of HRVDaoming Zhang0Cong Wang1Chuangye Li2Wei Dai3China University of Mining and TechnologyChina University of Mining and TechnologyChina University of Mining and TechnologyChina University of Mining and TechnologyElectrocardiogram is a comprehensive reflection of cardiac electrical activity on the surface of the body. It is of great research value to analyse ECG signals and diagnose heart diseases. Since the heartbeat process is a chaotic system, this study proposes a multi-fractal detrended fluctuation half-spectrum analysis method of short-term heart rate variability-y (HRV) signals from the perspective of non-linear dynamics, for patients with normal heart rate, sporadic heart rate variation and supraventricular rate, the heart rate mutation signal of patients with heart rate variation is calculated, and the statistical value distribution of multi-fractal parameter α has a certain change trend with the change of disease condition. The classification accuracy can reach >75% through box plot analysis.https://digital-library.theiet.org/content/journals/10.1049/joe.2019.1067fractalsfluctuationsmedical signal processingelectrocardiographydiseasesstatistical distributionssignal classificationecg signalsheart diseasesmultifractal detrended fluctuation half-spectrum analysis methodshort-term heart rate variabilitynormal heart ratesporadic heart rate variationbox plot analysisclassification accuracydisease conditionstatistical value distributionnonlinear dynamicsheartbeat processelectrocardiogramcardiac electrical activitymultifractal parameterheart rate mutation signalsupraventricular rate |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Daoming Zhang Cong Wang Chuangye Li Wei Dai |
spellingShingle |
Daoming Zhang Cong Wang Chuangye Li Wei Dai Multi-fractal detrended fluctuation half-spectrum analysis of HRV The Journal of Engineering fractals fluctuations medical signal processing electrocardiography diseases statistical distributions signal classification ecg signals heart diseases multifractal detrended fluctuation half-spectrum analysis method short-term heart rate variability normal heart rate sporadic heart rate variation box plot analysis classification accuracy disease condition statistical value distribution nonlinear dynamics heartbeat process electrocardiogram cardiac electrical activity multifractal parameter heart rate mutation signal supraventricular rate |
author_facet |
Daoming Zhang Cong Wang Chuangye Li Wei Dai |
author_sort |
Daoming Zhang |
title |
Multi-fractal detrended fluctuation half-spectrum analysis of HRV |
title_short |
Multi-fractal detrended fluctuation half-spectrum analysis of HRV |
title_full |
Multi-fractal detrended fluctuation half-spectrum analysis of HRV |
title_fullStr |
Multi-fractal detrended fluctuation half-spectrum analysis of HRV |
title_full_unstemmed |
Multi-fractal detrended fluctuation half-spectrum analysis of HRV |
title_sort |
multi-fractal detrended fluctuation half-spectrum analysis of hrv |
publisher |
Wiley |
series |
The Journal of Engineering |
issn |
2051-3305 |
publishDate |
2019-11-01 |
description |
Electrocardiogram is a comprehensive reflection of cardiac electrical activity on the surface of the body. It is of great research value to analyse ECG signals and diagnose heart diseases. Since the heartbeat process is a chaotic system, this study proposes a multi-fractal detrended fluctuation half-spectrum analysis method of short-term heart rate variability-y (HRV) signals from the perspective of non-linear dynamics, for patients with normal heart rate, sporadic heart rate variation and supraventricular rate, the heart rate mutation signal of patients with heart rate variation is calculated, and the statistical value distribution of multi-fractal parameter α has a certain change trend with the change of disease condition. The classification accuracy can reach >75% through box plot analysis. |
topic |
fractals fluctuations medical signal processing electrocardiography diseases statistical distributions signal classification ecg signals heart diseases multifractal detrended fluctuation half-spectrum analysis method short-term heart rate variability normal heart rate sporadic heart rate variation box plot analysis classification accuracy disease condition statistical value distribution nonlinear dynamics heartbeat process electrocardiogram cardiac electrical activity multifractal parameter heart rate mutation signal supraventricular rate |
url |
https://digital-library.theiet.org/content/journals/10.1049/joe.2019.1067 |
work_keys_str_mv |
AT daomingzhang multifractaldetrendedfluctuationhalfspectrumanalysisofhrv AT congwang multifractaldetrendedfluctuationhalfspectrumanalysisofhrv AT chuangyeli multifractaldetrendedfluctuationhalfspectrumanalysisofhrv AT weidai multifractaldetrendedfluctuationhalfspectrumanalysisofhrv |
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