Quantitative Poincar� plot analysis of heart rate variability: effect of endurance training

2004 ◽  
Vol 91 (1) ◽  
pp. 79-87 ◽  
Author(s):  
Laurent Mourot ◽  
Malika Bouhaddi ◽  
St�phane Perrey ◽  
Jean-Denis Rouillon ◽  
Jacques Regnard
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Endurance Training ◽  
Plot Analysis

Heart Rate Variability as a Predictor of Individual Adaptation to Endurance Training

2014 ◽  
Vol 46 ◽  
pp. 888
Author(s):  
Ville Vesterinen ◽  
Keijo Häkkinen ◽  
Tanja Laine ◽  
Esa Hynynen ◽  
Jussi Mikkola ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Endurance Training

Characterization of HRV by Poincare Plot Analysis among the Female Tea Garden Workers of Northern Hilly Regions of West Bengal

2012 ◽  
pp. 206-215
Author(s):  
Somsirsa Chatterjee ◽  
Ankur Ganguly ◽  
Saugat Bhattacharya
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
West Bengal ◽  
Mean Value ◽  
Short Term ◽  
Poincaré Plot ◽  
Plot Analysis ◽  
Tea Garden

Recent research on Heart Rate Variability (HRV) has proven that Poincare Plot is a powerful tool to mark Short Term and Long Term Heart Rate Variability. This study focuses a comprehensive characterization of HRV among the Tea Garden Workers of the Northern Hilly Regions of West Bengal. The characterization, as available from the data sets, projects the average values of SD1 characteristics, that is, Short Term HRV in females as 58.265ms and SD2 as 149.474. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. ApEn Characterization showed mean value of 0.961 and standard deviation of 0.274.

Segmented Poincaré Plot Analysis for Risk Stratification in Patients with Dilated Cardiomyopathy

2010 ◽  
Vol 49 (05) ◽  
pp. 511-515 ◽  
Author(s):  
C. Fischer ◽  
R. Schroeder ◽  
H. R. Figulla ◽  
M. Goernig ◽  
A. Voss
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Risk Stratification ◽  
Dilated Cardiomyopathy ◽  
Heart Rate Variability Analysis ◽  
Poincaré Plot ◽  
Plot Analysis ◽  
Interval Time Series ◽  
Nonlinear Features ◽  
Cloud Of Points

Summary Background: The prognostic value of heart rate variability in patients with dilated cardiomyopathy (DCM) is limited and does not contribute to risk stratification although the dynamics of ventricular repolarization differs considerably between DCM patients and healthy subjects. Neither linear nor nonlinear methods of heart rate variability analysis could discriminate between patients at high and low risk for sudden cardiac death. Objective: The aim of this study was to analyze the suitability of the new developed segmented Poincaré plot analysis (SPPA) to enhance risk stratification in DCM. Methods: In contrast to the usual applied Poincaré plot analysis the SPPA retains nonlinear features from investigated beat-to-beat interval time series. Main features of SPPA are the rotation of cloud of points and their succeeded variability depended segmentation. Results: Significant row and column probabilities were calculated from the segments and led to discrimination (up to p < 0.005) between low and high risk in DCM patients. Conclusion: For the first time an index from Poincaré plot analysis of heart rate variability was able to contribute to risk stratification in patients suffering from DCM.

Endurance training guided individually by daily heart rate variability measurements

2007 ◽  
Vol 101 (6) ◽  
pp. 743-751 ◽  
Author(s):  
Antti M. Kiviniemi ◽  
Arto J. Hautala ◽  
Hannu Kinnunen ◽  
Mikko P. Tulppo
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Endurance Training

Heart rate variability by Poincaré plot analysis in patients of essential hypertension and 12-week yoga therapy

2015 ◽  
Vol 5 (3) ◽  
pp. 174
Author(s):  
Punita Pushpanathan ◽  
Madanmohan Trakroo ◽  
R Swaminathan ◽  
Chandrasekar Madhavan
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Essential Hypertension ◽  
Yoga Therapy ◽  
Plot Analysis

Heart rate variability in prediction of individual adaptation to endurance training in recreational endurance runners

2011 ◽  
Vol 23 (2) ◽  
pp. 171-180 ◽  
Author(s):  
V. Vesterinen ◽  
K. Häkkinen ◽  
E. Hynynen ◽  
J. Mikkola ◽  
L. Hokka ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Endurance Training ◽  
Endurance Runners

Endurance Training and Heart Rate Variability (HRV)

2011 ◽  
Vol 43 (Suppl 1) ◽  
pp. 564-565
Author(s):  
Christa Janse van Rensburg ◽  
Catharina C. Grant ◽  
Lizelle Fletcher
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Endurance Training

Training-Load-Guided vs Standardized Endurance Training in Recreational Runners

2017 ◽  
Vol 12 (3) ◽  
pp. 295-303 ◽  
Author(s):  
Moritz Schumann ◽  
Javier Botella ◽  
Laura Karavirta ◽  
Keijo Häkkinen
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Oxygen Consumption ◽  
Endurance Training ◽  
Maximal Oxygen Consumption ◽  
Endurance Performance ◽  
Training Load ◽  
Training Volume ◽  
Treadmill Test ◽  
Recreational Runners

Purpose:To compare the effects of a standardized endurance-training program with individualized endurance training modified based on the cumulative training load provided by the Polar training-load feature.Methods:After 12 wk of similar training, 24 recreationally endurance-trained men were matched to a training-load-guided (TL, n = 10) or standardized (ST, n = 14) group and continued training for 12 wk. In TL, training sessions were individually chosen daily based on an estimated cumulative training load, whereas in ST the training was standardized with 4–6 sessions/wk. Endurance performance (shortest 1000-m running time during an incremental field test of 6 × 1000 m) and heart-rate variability (HRV) were measured every 4 wk, and maximal oxygen consumption (VO2max) was measured during an incremental treadmill test every 12 wk.Results:During weeks 1–12, similar changes in VO2max and 1000-m time were observed in TL (+7% ± 4%, P = .004 and –6% ± 4%, P = .069) and ST (+5% ± 7%, P = .019 and –8% ± 5%, P < .001). During wk 13–24, VO2max statistically increased in ST only (3% ± 4%, P = .034). The 1000-m time decreased in TL during wk 13–24 (–9% ± 5%, P = .011), but in ST only during wk 13–20 (–3% ± 2%, P = .003). The overall changes in VO2max and 1000-m time during wk 0–24 were similar in TL (+7% ± 4%, P = .001 and –9% ± 5%, P = .011) and ST (+10% ± 7%, P < .001 and –13% ± 5%, P < .001). No between-groups differences in total training volume and frequency were observed. HRV remained statistically unaltered in both groups.Conclusions:The main finding was that training performed according to the cumulative training load led to improvements in endurance performance similar to those with standardized endurance training in recreational endurance runners.

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