Literature DB >> 15848268

Correlation dimension analysis of heart rate variability in patients with dilated cardiomyopathy.

Raúl Carvajal1, Niels Wessel, Montserrat Vallverdú, Pere Caminal, Andreas Voss.   

Abstract

A correlation dimension analysis of heart rate variability (HRV) was applied to a group of 55 patients with dilated cardiomyopathy (DCM) and 55 healthy subjects as controls. The 24-h RR time series for each subject was divided into segments of 10,000 beats to determine the correlation dimension (CD) per segment. A study of the influence of the time delay (lag) in the calculation of CD was performed. Good discrimination between both groups (p<0.005) was obtained with lag values of 5 or greater. CD values of DCM patients (8.4+/-1.9) were significantly lower than CD values for controls (9.5+/-1.9). An analysis of CD values of HRV showed that for healthy people, CD night values (10.6+/-1.8) were significant greater than CD day values (9.2+/-1.9), revealing a circadian rhythm. In DCM patients, this circadian rhythm was lost and there were no differences between CD values in day (8.8+/-2.4) and night (8.9+/-2.1).

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Year:  2005        PMID: 15848268     DOI: 10.1016/j.cmpb.2005.01.004

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  12 in total

1.  Analysis of the mobile phone effect on the heart rate variability by using the largest Lyapunov exponent.

Authors:  Derya Yılmaz; Metin Yıldız
Journal:  J Med Syst       Date:  2009-06-18       Impact factor: 4.460

2.  Cloud-Based Smart Health Monitoring System for Automatic Cardiovascular and Fall Risk Assessment in Hypertensive Patients.

Authors:  P Melillo; A Orrico; P Scala; F Crispino; L Pecchia
Journal:  J Med Syst       Date:  2015-08-15       Impact factor: 4.460

3.  Circadian variation of motor current observed in fixed rotation speed continuous-flow left ventricular assist device support.

Authors:  Kenji Suzuki; Tomohiro Nishinaka; Takuma Miyamoto; Yuki Ichihara; Kenji Yamazaki
Journal:  J Artif Organs       Date:  2014-04-09       Impact factor: 1.731

4.  Correlation dimension analysis of Doppler signals in children with aortic valve disorders.

Authors:  Derya Yılmaz; N Fatma Güler
Journal:  J Med Syst       Date:  2009-05-15       Impact factor: 4.460

5.  Time-specific associations of wearable sensor-based cardiovascular and behavioral readouts with disease phenotypes in the outpatient setting of the Chronic Renal Insufficiency Cohort.

Authors:  Nicholas F Lahens; Mahboob Rahman; Jordana B Cohen; Debbie L Cohen; Jing Chen; Matthew R Weir; Harold I Feldman; Gregory R Grant; Raymond R Townsend; Carsten Skarke; And The Cric Study Investigators
Journal:  Digit Health       Date:  2022-06-16

6.  Automatic classifier based on heart rate variability to identify fallers among hypertensive subjects.

Authors:  Paolo Melillo; Alan Jovic; Nicola De Luca; Leandro Pecchia
Journal:  Healthc Technol Lett       Date:  2015-07-02

7.  Automated detection of anesthetic depth levels using chaotic features with artificial neural networks.

Authors:  V Lalitha; C Eswaran
Journal:  J Med Syst       Date:  2007-12       Impact factor: 4.460

8.  Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination.

Authors:  Paolo Melillo; Marcello Bracale; Leandro Pecchia
Journal:  Biomed Eng Online       Date:  2011-11-07       Impact factor: 2.819

9.  Automatic prediction of cardiovascular and cerebrovascular events using heart rate variability analysis.

Authors:  Paolo Melillo; Raffaele Izzo; Ada Orrico; Paolo Scala; Marcella Attanasio; Marco Mirra; Nicola De Luca; Leandro Pecchia
Journal:  PLoS One       Date:  2015-03-20       Impact factor: 3.240

Review 10.  A Review on the Nonlinear Dynamical System Analysis of Electrocardiogram Signal.

Authors:  Suraj K Nayak; Arindam Bit; Anilesh Dey; Biswajit Mohapatra; Kunal Pal
Journal:  J Healthc Eng       Date:  2018-05-02       Impact factor: 2.682

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