Literature DB >> 18368501

Influence of ECG sampling frequency on spectral analysis of RR intervals and baroreflex sensitivity using the EUROBAVAR data set.

Tjalf Ziemssen1, Julia Gasch, Heinz Ruediger.   

Abstract

To evaluate the impact of different ECG sampling frequencies on parameters of spectral and baroreflex analysis. Spectral and baroreflex analyses were performed in the EUROBAVAR data set (46 recordings of 23 persons) using the original ECG sampling frequency of 500 Hz and - simulated - sampling frequencies of 200 and 100 Hz. For this analysis, the technique of trigonometric regressive spectral (TRS) analysis was used. In the standing position, there were no statistically significant differences in baroreflex sensitivity and frequency bands ranging from VLF to HF using 100 Hz instead of the original 500 Hz. Only the UHF band (>0.40 Hz) was significantly different. In the supine position, similar results could be described for 100 Hz, although there were slight, but significant (P < 0.05) changes in baroreflex sensitivity of around 1 ms/mmHg at the simulated 100 Hz. Using a simulated 200 Hz instead of a 500 Hz sampling frequency had no significant impact on the spectral and baroreflex parameters. The probability to demonstrate an impact of different ECG sampling frequencies was higher in people with pathologically decreased variability of RR intervals. In most of the cases, it is sufficient for spectral and baroreflex analysis by TRS to use data with an ECG sampling frequency of 100 Hz in comparison to 500 Hz. Only if there is a pathologically decreased variability of RR intervals in patients, spectral and baroreflex parameters could be significantly influenced by lower ECG sampling frequencies of up to 100 Hz, but only to a minor degree.

Entities:  

Mesh:

Year:  2008        PMID: 18368501     DOI: 10.1007/s10877-008-9117-0

Source DB:  PubMed          Journal:  J Clin Monit Comput        ISSN: 1387-1307            Impact factor:   2.502


  23 in total

1.  The trigonometric regressive spectral analysis--a method for mapping of beat-to-beat recorded cardiovascular parameters on to frequency domain in comparison with Fourier transformation.

Authors:  H Rüdiger; L Klinghammer; K Scheuch
Journal:  Comput Methods Programs Biomed       Date:  1999-01       Impact factor: 5.428

2.  Comparison of various techniques used to estimate spontaneous baroreflex sensitivity (the EuroBaVar study).

Authors:  Dominique Laude; Jean-Luc Elghozi; Arlette Girard; Elisabeth Bellard; Malika Bouhaddi; Paolo Castiglioni; Catherine Cerutti; Andrei Cividjian; Marco Di Rienzo; Jacques-Olivier Fortrat; Ben Janssen; John M Karemaker; Georges Lefthériotis; Gianfranco Parati; Pontus B Persson; Alberto Porta; Luc Quintin; Jacques Regnard; Heinz Rüdiger; Harald M Stauss
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2003-09-18       Impact factor: 3.619

3.  Quantifying errors in spectral estimates of HRV due to beat replacement and resampling.

Authors:  Gari D Clifford; Lionel Tarassenko
Journal:  IEEE Trans Biomed Eng       Date:  2005-04       Impact factor: 4.538

4.  Sampling frequency of the electrocardiogram for spectral analysis of the heart rate variability.

Authors:  M Merri; D C Farden; J G Mottley; E L Titlebaum
Journal:  IEEE Trans Biomed Eng       Date:  1990-01       Impact factor: 4.538

5.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology.

Authors: 
Journal:  Eur Heart J       Date:  1996-03       Impact factor: 29.983

Review 6.  Heart rate variability: origins, methods, and interpretive caveats.

Authors:  G G Berntson; J T Bigger; D L Eckberg; P Grossman; P G Kaufmann; M Malik; H N Nagaraja; S W Porges; J P Saul; P H Stone; M W van der Molen
Journal:  Psychophysiology       Date:  1997-11       Impact factor: 4.016

7.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

Review 8.  Spectral analysis of blood pressure and heart rate variability in evaluating cardiovascular regulation. A critical appraisal.

Authors:  G Parati; J P Saul; M Di Rienzo; G Mancia
Journal:  Hypertension       Date:  1995-06       Impact factor: 10.190

9.  [Minimal interval length for safe determination of brief heart rate variability].

Authors:  M Pelzer; D Hafner; G Arnold; J D Schipke
Journal:  Z Kardiol       Date:  1995-12

10.  Hemodynamic regulation: investigation by spectral analysis.

Authors:  S Akselrod; D Gordon; J B Madwed; N C Snidman; D C Shannon; R J Cohen
Journal:  Am J Physiol       Date:  1985-10
View more
  17 in total

Review 1.  Trigonometric regressive spectral analysis: an innovative tool for evaluating the autonomic nervous system.

Authors:  Tjalf Ziemssen; Manja Reimann; Julia Gasch; Heinz Rüdiger
Journal:  J Neural Transm (Vienna)       Date:  2013-06-28       Impact factor: 3.575

2.  Baroreflex sensitivity and power spectral analysis in different extrapyramidal syndromes.

Authors:  C Friedrich; H Rüdiger; C Schmidt; B Herting; S Prieur; S Junghanns; K Schweitzer; C Globas; L Schöls; D Berg; H Reichmann; T Ziemssen
Journal:  J Neural Transm (Vienna)       Date:  2008-09-20       Impact factor: 3.575

3.  Comparison of three mobile devices for measuring R-R intervals and heart rate variability: Polar S810i, Suunto t6 and an ambulatory ECG system.

Authors:  Matthias Weippert; Mohit Kumar; Steffi Kreuzfeld; Dagmar Arndt; Annika Rieger; Regina Stoll
Journal:  Eur J Appl Physiol       Date:  2010-03-12       Impact factor: 3.078

4.  Comparison of baroreflex sensitivity estimated from ECG R-R and inter-systolic intervals obtained by finger plethysmography and radial tonometry.

Authors:  Juliane Viehweg; Manja Reimann; Julia Gasch; Heinz Rüdiger; Tjalf Ziemssen
Journal:  J Neural Transm (Vienna)       Date:  2016-03-17       Impact factor: 3.575

5.  Reliability of the Parabola Approximation Method in Heart Rate Variability Analysis Using Low-Sampling-Rate Photoplethysmography.

Authors:  Hyun Jae Baek; JaeWook Shin; Gunwoo Jin; Jaegeol Cho
Journal:  J Med Syst       Date:  2017-10-24       Impact factor: 4.460

6.  Sympathetic cardiovascular hyperactivity precedes brain death.

Authors:  Harald Marthol; Tassanai Intravooth; Jürgen Bardutzky; Philip De Fina; Stefan Schwab; Max J Hilz
Journal:  Clin Auton Res       Date:  2010-05-12       Impact factor: 4.435

7.  Heart rate variability during wakefulness as a marker of obstructive sleep apnea severity.

Authors:  Hua Qin; Brendan T Keenan; Diego R Mazzotti; Fernando Vaquerizo-Villar; Jan F Kraemer; Niels Wessel; Sergio Tufik; Lia Bittencourt; Peter A Cistulli; Philip de Chazal; Kate Sutherland; Bhajan Singh; Allan I Pack; Ning-Hung Chen; Ingo Fietze; Thorarinn Gislason; Steven Holfinger; Ulysses J Magalang; Thomas Penzel
Journal:  Sleep       Date:  2021-05-14       Impact factor: 5.849

8.  Trigonometric regressive spectral analysis reliably maps dynamic changes in baroreflex sensitivity and autonomic tone: the effect of gender and age.

Authors:  Manja Reimann; Constanze Friedrich; Julia Gasch; Heinz Reichmann; Heinz Rüdiger; Tjalf Ziemssen
Journal:  PLoS One       Date:  2010-08-16       Impact factor: 3.240

9.  Determination of baroreflex sensitivity during the modified Oxford maneuver by trigonometric regressive spectral analysis.

Authors:  Julia Gasch; Manja Reimann; Heinz Reichmann; Heinz Rüdiger; Tjalf Ziemssen
Journal:  PLoS One       Date:  2011-03-18       Impact factor: 3.240

10.  Association between short-term heart rate variability and blood coagulation in patients with breast cancer.

Authors:  Lingling Wang; Jingfeng Wang; Peng Li; Xiangzhi Wang; Shuang Wu; Bo Shi
Journal:  Sci Rep       Date:  2021-07-29       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.