Demonstration of nonlinear components in heart rate variability of healthy persons

1998 ◽  
Vol 275 (5) ◽  
pp. H1577-H1584 ◽  
Author(s):  
Christian Braun ◽  
Peter Kowallik ◽  
Ansgar Freking ◽  
Dörte Hadeler ◽  
Klaus-Dietrich Kniffki ◽  
...  

We present a systematic approach for detecting nonlinear components in heart rate variability (HRV). The analysis is based on twenty-three 48-h Holter recordings in healthy persons during sinus rhythm. Although many segments of 1,024 R-R intervals are stationary, only few stationary segments of 8,192–32,768 R-R intervals can be found using a test of Isliker and Kurths ( Int. J. Bifurcation Chaos 3:1573–1579, 1993.). By comparing the correlation integrals from these segments and corresponding surrogate data sets, we reject the null hypothesis that these time series are realization of linear processes. On the basis of a test statistic exploring the differences of consecutive R-R intervals, we reject the hypothesis that the R-R intervals represent a static transformation of a linear process using optimized surrogate data. Furthermore, time irreversibility of the heartbeat data is demonstrated. We interpret these results as a strong evidence for nonlinear components in HRV. Thus R-R intervals from healthy persons contain more information than can be extracted by linear analysis in the time and frequency domain.

2002 ◽  
Vol 12 (12) ◽  
pp. 2967-2976 ◽  
Author(s):  
ZHENYA HE ◽  
WENJIANG PEI ◽  
LUXI YANG ◽  
STEPHEN S. HULL ◽  
JOHN Y. CHEUNG

The control of heart rate is primarily due to the function of the human autonomic nervous system. This process is deterministic but highly nonlinear. Due to the rapid response of the central nervous system, the actual heart rate is adjusted on a beat-to-beat basis. In this study, we propose the use of the cluster-weighted filtering (CWF) method to model the underlying deterministic mechanism of the variation of heart intervals. On a gross scale, a Gaussian network is used for function approximation to model the overall complex nonlinear dynamics of heart rate variability. At the same time, a noise reduction strategy based on Bayesian theory is used to eliminate the effects of noise on a finer scale. The algorithm iteratively models the nonlinear dynamics and reduces the noise components simultaneously. The proposed algorithm has been applied to 19 real data sets selected for analysis. The system dynamics was modeled from the experimental data sets. Based on the criterion for reconstruction used in this letter, the results suggested that the underlying deterministic dynamics could be reconstructed. A number of additional tests such as surrogate data and the largest Lyapunov exponent analyses were also carried out. Results confirmed that heart rate variability is a highly nonlinear process. It is further observed that the underlying deterministic mechanism of cardiac dynamics is highly sensitive to the initial conditions.


Author(s):  
Somsirsa Chatterjee ◽  
Ankur Ganguly ◽  
Saugat Bhattacharya

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.


2002 ◽  
Vol 18 (1) ◽  
pp. 119-139 ◽  
Author(s):  
Qiying Wang ◽  
Yan-Xia Lin ◽  
Chandra M. Gulati

Let Xt be a linear process defined by Xt = [sum ]k=0∞ ψkεt−k, where {ψk, k ≥ 0} is a sequence of real numbers and {εk, k = 0,±1,±2,...} is a sequence of random variables. Two basic results, on the invariance principle of the partial sum process of the Xt converging to a standard Wiener process on [0,1], are presented in this paper. In the first result, we assume that the innovations εk are independent and identically distributed random variables but do not restrict [sum ]k=0∞ |ψk| < ∞. We note that, for the partial sum process of the Xt converging to a standard Wiener process, the condition [sum ]k=0∞ |ψk| < ∞ or stronger conditions are commonly used in previous research. The second result is for the situation where the innovations εk form a martingale difference sequence. For this result, the commonly used assumption of equal variance of the innovations εk is weakened. We apply these general results to unit root testing. It turns out that the limit distributions of the Dickey–Fuller test statistic and Kwiatkowski, Phillips, Schmidt, and Shin (KPSS) test statistic still hold for the more general models under very weak conditions.


Author(s):  
Diana Piper ◽  
Karin Schiecke ◽  
Lutz Leistritz ◽  
Britta Pester ◽  
Franz Benninger ◽  
...  

AbstractAn innovative concept for synchronization analysis between heart rate (HR) components and rhythms in EEG envelopes is represented; it applies time-variant analyses to heart rate variability (HRV) and EEG, and it was tested in children with temporal lobe epilepsy (TLE). After a removal of ocular and movement-related artifacts, EEG band activity was computed by means of the frequency-selective Hilbert transform providing envelopes of frequency bands. Synchronization between HRV and EEG envelopes was quantified by Morlet wavelet coherence. A surrogate data approach was adapted to test for statistical significance of time-variant coherences. Using this processing scheme, significant coherence values between a HRV low-frequency sub-band (0.08–0.12 Hz) and the EEG δ envelope (1.5–4 Hz) occurring both in the preictal and early postictal periods of a seizure can be shown. Investigations were performed for all electrodes at 20-s intervals and for selected electrode pairs (T3÷C3, T4÷C4) in a time-variant mode. Synchronization was more pronounced in the group of right hemispheric TLE patients than in the left hemispheric group. Such a group-specific augmentation of synchronization confirms the hypothesis of a right hemispheric lateralization of sympathetic cardiac control of the low-frequency HRV components.


1994 ◽  
Vol 77 (6) ◽  
pp. 2863-2869 ◽  
Author(s):  
A. L. Goldberger ◽  
J. E. Mietus ◽  
D. R. Rigney ◽  
M. L. Wood ◽  
S. M. Fortney

Head-down bed rest is used to model physiological changes during spaceflight. We postulated that bed rest would decrease the degree of complex physiological heart rate variability. We analyzed continuous heart rate data from digitized Holter recordings in eight healthy female volunteers (age 28–34 yr) who underwent a 13-day 6 degree head-down bed rest study with serial lower body negative pressure (LBNP) trials. Heart rate variability was measured on 4-min data sets using conventional time and frequency domain measures as well as with a new measure of signal “complexity” (approximate entropy). Data were obtained pre-bed rest (control), during bed rest (day 4 and day 9 or 11), and 2 days post-bed rest (recovery). Tolerance to LBNP was significantly (P < 0.02) reduced on both bed rest days vs. pre-bed rest. Heart rate variability was assessed at peak LBNP. Heart rate approximate entropy was significantly (P < 0.05) decreased at day 4 and day 9 or 11, returning toward normal during recovery. Heart rate standard deviation and the ratio of high- to low-power frequency did not change significantly. We conclude that short-term bed rest is associated with a decrease in the complex variability of heart rate during LBNP testing in healthy young adult women. Measurement of heart rate complexity, using a method derived from nonlinear dynamics (“chaos theory”), may provide a sensitive marker of this loss of physiological variability, complementing conventional time and frequency domain statistical measures.


10.2196/17355 ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. e17355
Author(s):  
Emily Lam ◽  
Shahrose Aratia ◽  
Julian Wang ◽  
James Tung

Background Heart rate variability (HRV) is used to assess cardiac health and autonomic nervous system capabilities. With the growing popularity of commercially available wearable technologies, the opportunity to unobtrusively measure HRV via photoplethysmography (PPG) is an attractive alternative to electrocardiogram (ECG), which serves as the gold standard. PPG measures blood flow within the vasculature using color intensity. However, PPG does not directly measure HRV; it measures pulse rate variability (PRV). Previous studies comparing consumer-grade PRV with HRV have demonstrated mixed results in short durations of activity under controlled conditions. Further research is required to determine the efficacy of PRV to estimate HRV under free-living conditions. Objective This study aims to compare PRV estimates obtained from a consumer-grade PPG sensor with HRV measurements from a portable ECG during unsupervised free-living conditions, including sleep, and examine factors influencing estimation, including measurement conditions and simple editing methods to limit motion artifacts. Methods A total of 10 healthy adults were recruited. Data from a Microsoft Band 2 and a Shimmer3 ECG unit were recorded simultaneously using a smartphone. Participants wore the devices for >90 min during typical day-to-day activities and while sleeping. After filtering, ECG data were processed using a combination of discrete wavelet transforms and peak-finding methods to identify R-R intervals. P-P intervals were edited for deletion using methods based on outlier detection and by removing sections affected by motion artifacts. Common HRV metrics were compared, including mean N-N, SD of N-N intervals, percentage of subsequent differences >50 ms (pNN50), root mean square of successive differences, low-frequency power (LF), and high-frequency power. Validity was assessed using root mean square error (RMSE) and Pearson correlation coefficient (R2). Results Data sets for 10 days and 9 corresponding nights were acquired. The mean RMSE was 182 ms (SD 48) during the day and 158 ms (SD 67) at night. R2 ranged from 0.00 to 0.66, with 2 of 19 (2 nights) trials considered moderate, 7 of 19 (2 days, 5 nights) fair, and 10 of 19 (8 days, 2 nights) poor. Deleting sections thought to be affected by motion artifacts had a minimal impact on the accuracy of PRV measures. Significant HRV and PRV differences were found for LF during the day and R-R, SDNN, pNN50, and LF at night. For 8 of the 9 matched day and night data sets, R2 values were higher at night (P=.08). P-P intervals were less sensitive to rapid R-R interval changes. Conclusions Owing to overall poor concurrent validity and inconsistency among participant data, PRV was found to be a poor surrogate for HRV under free-living conditions. These findings suggest that free-living HRV measurements would benefit from examining alternate sensing methods, such as multiwavelength PPG and wearable ECG.


2019 ◽  
Author(s):  
Emily Lam ◽  
Shahrose Aratia ◽  
Julian Wang ◽  
James Tung

BACKGROUND Heart rate variability (HRV) is used to assess cardiac health and autonomic nervous system capabilities. With the growing popularity of commercially available wearable technologies, the opportunity to unobtrusively measure HRV via photoplethysmography (PPG) is an attractive alternative to electrocardiogram (ECG), which serves as the gold standard. PPG measures blood flow within the vasculature using color intensity. However, PPG does not directly measure HRV; it measures pulse rate variability (PRV). Previous studies comparing consumer-grade PRV with HRV have demonstrated mixed results in short durations of activity under controlled conditions. Further research is required to determine the efficacy of PRV to estimate HRV under free-living conditions. OBJECTIVE This study aims to compare PRV estimates obtained from a consumer-grade PPG sensor with HRV measurements from a portable ECG during unsupervised free-living conditions, including sleep, and examine factors influencing estimation, including measurement conditions and simple editing methods to limit motion artifacts. METHODS A total of 10 healthy adults were recruited. Data from a Microsoft Band 2 and a Shimmer3 ECG unit were recorded simultaneously using a smartphone. Participants wore the devices for &gt;90 min during typical day-to-day activities and while sleeping. After filtering, ECG data were processed using a combination of discrete wavelet transforms and peak-finding methods to identify R-R intervals. P-P intervals were edited for deletion using methods based on outlier detection and by removing sections affected by motion artifacts. Common HRV metrics were compared, including mean N-N, SD of N-N intervals, percentage of subsequent differences &gt;50 ms (pNN50), root mean square of successive differences, low-frequency power (LF), and high-frequency power. Validity was assessed using root mean square error (RMSE) and Pearson correlation coefficient (<i>R</i><sup>2</sup>). RESULTS Data sets for 10 days and 9 corresponding nights were acquired. The mean RMSE was 182 ms (SD 48) during the day and 158 ms (SD 67) at night. <i>R</i><sup>2</sup> ranged from 0.00 to 0.66, with 2 of 19 (2 nights) trials considered moderate, 7 of 19 (2 days, 5 nights) fair, and 10 of 19 (8 days, 2 nights) poor. Deleting sections thought to be affected by motion artifacts had a minimal impact on the accuracy of PRV measures. Significant HRV and PRV differences were found for LF during the day and R-R, SDNN, pNN50, and LF at night. For 8 of the 9 matched day and night data sets, <i>R</i><sup>2</sup> values were higher at night (<i>P=</i>.08). P-P intervals were less sensitive to rapid R-R interval changes. CONCLUSIONS Owing to overall poor concurrent validity and inconsistency among participant data, PRV was found to be a poor surrogate for HRV under free-living conditions. These findings suggest that free-living HRV measurements would benefit from examining alternate sensing methods, such as multiwavelength PPG and wearable ECG.


Author(s):  
O. V. Korkushko ◽  
V. P. Chyzhova ◽  
V. V. Kuznietsov ◽  
K. O. Apykhtin ◽  
N. M. Koshel ◽  
...  

Objective — to establish  the peculiarities and relationship of spectral indicators of heart rate variability (HRV), fasting glucose level and lipid profile indicators in practically healthy persons and in elderly patients with dyscirculatory atherosclerotic encephalopathy (DEP). Materials and methods. The study involved 77 subjects of various age, who were divided into two groups: group 1 consisted  of apparently  healthy persons (19  subjects of middle age and 27 elderly subjects) and group 2 that included patients with DAP manifestations (15 subjects of middle age and 16 elderly persons). In the groups of elderly persons, the subgroups were extracted based on the fasting glucose levels: lower than 6.1 mmol/l and 6.1 mmol/l. The measurements of systolic and diastolic blood pressure were performed in a sitting position after at least 10 min of rest. Plasma glucose levels were determined by a standard glucoseoxidase method, lipid profile was determined by using the automatic analyzer. To assess the risk of cardiovascular disease development, calculations were performed for the indices of the cardiovascular risk: Castelli index and Boizel index. All patients with DEP manifestations underwent 24‑hour Holter ECG monitoring, and healthy people underwent 5 min ECG. Results. The incidence of fasting hyperglycemia in patients with 1 — 2 stage DEP manifestations was in 3.4 times higher (p < 0.05) vs healthy subjects of the same age. The significant correlation has been reveled between age and HDL‑C (r = 0.47, р < 0.05), atherogenic index (r = –0.40, р < 0.05), heart rate (r = –0.45, р < 0.05), Castelli index (r = –0.40, р < 0.05), Boizel index (r = –0.31, р < 0.05), heart rate (r = –0.45, р < 0.05). Moreover, correlation has been established between Boizel index and heart rate (r = +0.44, р < 0.05), heart rate and LF/HF (r = +0.57, р < 0.05), between TG and heart rate (r = +0.43, р < 0.05), LF/HF (r = +0.53, р < 0.05) and between levels of very low density lipoprotein cholesterol and heart rate (r = +0.44 р < 0.05), LF/HF (r = +0.53, р < 0. 05). It has been established that hyperglycemia and dyslipidemia significantly affected spectral heart rate variability indices in patients with encephalopathy manifestations. Conclusions. With ageing, the frequency of fasting hyperglycemia in patients with 1 — 2 stage DEP manifestations was significantly higher in 3.4 times in comparison with practically healthy individuals of the same age. In the group of practically healthy persons over 60 years old, the tendency has been revealed towards a decrease in the spectral parameters of HRV LF and HF, which indicates HRV decrease. With the development of 1 — 2 stages DEP, even in the middle age, a significant decrease in the value of HF (parasympathetic influence) and a significant increase in the value of LF (sympathetic activity) were revealed. In elderly people with signs of 1 — 2 stage DEP with normoglycemia and fasting hyperglycemia against the background of dyslipidemia, the sympathetic link of the autonomic nervous system is activated, accompanied by an increase in the index of vascular complications. In patients with 1 — 2 stages DEP and fasting hyperglycemia, this tendency was even more pronounced. This fact can serve as confirmation that in the development of pre‑diabetic disorders (fasting hyperglycemia) one of the pathogenic mechanisms is the violation of the central regulatory mechanisms, which in turn leads to the violation of the autonomic balance with the prevalence of sympathicotonia, and a decrease in the parasympathetic effect on the heart, which leads to development of autonomous cardiac neuropathy.  


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