Methodological comparisons of heart rate variability analysis in patients with type 2 diabetes and angiotensin converting enzyme polymorphism

Angiotensin converting enzyme (ACE) polymorphism has been shown to be important in hypertension progression and also in diabetes complications, especially associated with heart disease. Heart rate variability (HRV) is an established measure for classification of autonomic function regulating heart rate, based on the interbeat interval time series derived from a raw ECG recording. Results of this paper show that the length (number of interbeat intervals) and preprocessing of the tachogram affect the HRV analysis outcome. The comparison was based on tachogram lengths of 250, 300, 350, and 400 RR-intervals and five preprocessing approaches. An automated adaptive preprocessing method for the heart rate biosignal and tachogram length of 400 interbeat intervals provided the best classification. HRV results differed for the Type 2 Diabetes Mellitus (T2DM) group between the I/I genotype and the I/D and D/D genotypes, whereas for controls there was no significant difference in HRV between genotypes. Selecting an appropriate length of recording and automated preprocessing has confirmed that there is an effect of ACE polymorphism including the I/I genotype and that I/I should not be combined with I/D genotype in determining the extent of autonomic modulation of the heart rate.

Multiple Spectral Peak Tracking for Heart Rate Monitoring from Photoplethysmography Signal During Intensive Physical Exercise

We propose a multiple initialization based spectral peak tracking (MISPT) technique for heart rate monitoring from photoplethysmography (PPG) signal. MISPT is applied on the PPG signal after removing the motion artifact using an adaptive noise cancellation filter. MISPT yields several estimates of the heart rate trajectory from the spectrogram of the denoised PPG signal which are finally combined using a novel measure called trajectory strength. Multiple initializations help in correcting erroneous heart rate trajectories unlike the typical SPT which uses only single initialization. Experiments on the PPG data from 12 subjects recorded during intensive physical exercise show that the MISPT based heart rate monitoring indeed yields a better heart rate estimate compared to the SPT with single initialization. On the 12 datasets MISPT results in an average absolute error of 1.11 BPM which is lower than 1.28 BPM obtained by the state-of-the-art online heart rate monitoring algorithm.

Application of higher order statistics/spectra in biomedical signals : a review

For many decades correlation and power spectrum have been primary tools for digital signal processing applications in the biomedical area. The information contained in the power spectrum is essentially that of the autocorrelation sequence; which is sufficient for complete statistical descriptions of Gaussian signals of known means. However, there are practical situations where one needs to look beyond autocorrelation of a signal to extract information regarding deviation from Gaussianity and the presence of phase relations. Higher order spectra, also known as polyspectra, are spectral representations of higher order statistics, i.e. moments and cumulants of third order and beyond. HOS (higher order statistics or higher order spectra) can detect deviations from linearity, stationarity or Gaussianity in the signal. Most of the biomedical signals are non-linear, non-stationary and non-Gaussian in nature and therefore it can be more advantageous to analyze them with HOS compared to the use of second order correlations and power spectra. In this paper we have discussed the application of HOS for different bio-signals. HOS methods of analysis are explained using a typical heart rate variability (HRV) signal and applications to other signals are reviewed.

Recovery of linear and nonlinear heart rate dynamics after coronary artery bypass grafting surgery

Background: Conventional coronary artery bypass grafting (C-CABG) and off-pump CABG (OPCAB) surgery may produce different patients' outcomes, including the extent of cardiac autonomic (CA) imbalance. the beneficial effects of an exercise-based inpatient programme on heart rate variability (HRV) for C-CABG patients have already been demonstrated by our group. However, there are no studies about the impact of a cardiac rehabilitation (CR) on HRV behaviour after OPCAB. the aim of this study is to compare the influence of both operative techniques on HRV pattern following CR in the postoperative (PO) period.Methods: Cardiac autonomic function was evaluated by HRV indices pre- and post-CR in patients undergoing C-CABG (n = 15) and OPCAB (n = 13). All patients participated in a short-term(approximately 5 days) supervised CR programme of early mobilization, consisting of progressive exercises, from active-assistive movements at PO day 1 to climbing flights of stairs at PO day 5.Results: Both groups demonstrated a reduction in HRV following surgery. the CR programme promoted improvements in HRV indices at discharge for both groups. the OPCAB group presented with higher HRV values at discharge, compared to the C-CABG group, indicating a better recovery of CA function.Conclusion: Our data suggest that patients submitted to OPCAB and an inpatient CR programme present with greater improvement in CA function compared to C-CABG.

Impact of obesity on autonomic modulation, heart rate and blood pressure in obese young people

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Major depression with ischemic heart disease: Effects of paroxetine and nortriptyline on measures of nonlinearity and chaos of heart rate

Depression is associated with increased cardiovascular mortality in patients with preexisting cardiac illness. A decrease in cardiac vagal function as suggested by a decrease in heart rate variability (HRV) or heart period variability has been linked to sudden death in patients with cardiac disease as well as in normal controls. Recent studies have shown decreased vagal function in cardiac patients with depression as well as in depressed patients without cardiac illness. In this study, we compared 20 h awake and sleep heart period nonlinear measures using quantification of nonlinearity and chaos in two groups of patients with major depression and ischemic heart disease (mean age 59-60 years) before and after 6 weeks of treatment with paroxetine or nortriptyline. Patients received paroxetine, 20-30 mg/day or nortriptyline targeted to 190-570 nmol/l for 6 weeks. For HRV analysis, 24 patients were included in the paroxetine treatment study and 20 patients in the nortriptyline study who had at least 20,000 s of awake data. The ages of these groups were 60.4 +/- 10.5 years for paroxetine and 60.8 +/- 13.4 years for nortriptyline. There was a significant decrease in the largest Lyapunov exponent (LLE) after treatment with nortriptyline but not paroxetine. There were also significant decreases in nonlinearity scores on S-netPR and S-netGS after nortriptyline, which may be due to a decrease in cardiac vagal modulation of HRV. S-netGS and awake LLE were the most significant variables that contributed to the discrimination of postparoxetine and postnortriptyline groups even with the inclusion of time and frequency domain measures. These findings suggest that nortriptyline decreases the measures of chaos probably through its stronger vagolytic effects on cardiac autonomic function compared with paroxetine, which is in agreement with previous clinical and preclinical reports. Nortriptyline was also associated with a significant decrease in nonlinearity scores, which may be due to anticholinergic and/or sympatholytic effects. As depression is associated with a strong risk factor for cardiovascular mortality, one should be careful about using any drug that adversely affects cardiac vagal function. Copyright (C) 2002 S. Karger AG, Basel.

Blind equalization of nonminimum phase channels: higher order cumulant based algorithm

Higher order cumulant analysis is applied to the blind equalization of linear time-invariant (LTI) nonminimum-phase channels. The channel model is moving-average based. To identify the moving average parameters of channels, a higher-order cumulant fitting approach is adopted in which a novel relay algorithm is proposed to obtain the global solution. In addition, the technique incorporates model order determination. The transmitted data are considered as independently identically distributed random variables over some discrete finite set (e.g., set {±1, ±3}). A transformation scheme is suggested so that third-order cumulant analysis can be applied to this type of data. Simulation examples verify the feasibility and potential of the algorithm. Performance is compared with that of the noncumulant-based Sato scheme in terms of the steady state MSE and convergence rate.

Analysis of fetal heart rate asymmetry before and after 35 weeks of gestation

In this study, we have investigated the evidence of fetal heart rate asymmetry and how the fetal heart rate asymmetry changes before and after 35 weeks of gestation. Noninvasive fetal electrocardiogram (fECG) signals from 45 pregnant women at the gestational age from16 to 41 weeks with normal single pregnancies were analysed. A nonlinear parameter called heart rate asymmetry (HRA) index that measures time asymmetry of RR interval time-series signal was used to understand the changes of HRA in early and late fetus groups. Results indicate that fetal HRA measured by Porta's Index (PI) consistently increases after 35 weeks gestation compared to foetus before 32 weeks of gestation. It might be due to significant changes of sympatho-vagal balance towards delivery with more sympathetic surge. On the other hand, Guzik's Index (GI) showed a mixed effect i.e., increases at lower lags and decreases at higher lags. Finally, fHRA could potentially help identify normal and the pathological autonomic nervous system development.

The effect of eccentric strength training on heart rate and on its variability during isometric exercise in healthy older men

The purpose of this study was to investigate if chronic eccentric strength training (ST) affects heart rate (HR) and heart rate variability (HRV) during sub-maximal isometric voluntary contractions (SIVC). The training group (TG) (9 men, 62 ± 2) was submitted to ST (12 weeks, 2 days/week, 2 - 4 sets of 8-12 repetitions at 75-80% peak torque (PT). The control group (CG) (8 men, 64 ± 4) did not perform ST. The HR and the HRV (RMSSD index) were evaluated during SIVC of the knee extension (15, 30 and 40% of PT). ST increased the eccentric torque only in TG, but did not change the isometric PT and the duration of SIVC. During SIVC, the HR response pattern and the RMSSD index were similar for both groups in pre- and post-training evaluations. Although ST increased the eccentric torque in the TG, it did not generate changes in HR or HRV. © Springer-Verlag 2008.

An exploration of heart rate response to differing music rhythm and tempos

The aim of this study was to investigate acute cardiac response and heart rate variability (HRV) when listening to differing forms of music. Eleven healthy men aged between 18 and 25 years old were included in the study. HRV was recorded at rest for ten minutes with no music, then were asked to listen to classical baroque or heavy metal music for a period of 20 min. It was noted that heart rate variability did not affect HRV indices for time and frequency. In conclusion, music with different tempos does not influence cardiac autonomic regulation in men. However more studies are suggested to explore this topic in greater detail.

Acute effects of flexible pole exercise on heart rate dynamics

Introduction: Exercise with flexible poles provides fast eccentric and concentric muscle contractions. Although the literature reports significant muscle chain activity during this exercise, it is not clear if a single bout of exercise induces cardiac changes. In this study we assessed the acute effects of flexible pole exercise on cardiac autonomic regulation.Methods: The study was performed on 22 women between 18 and 26 years old. We assessed heart rate variability (HRV) in the time (SDNN, RMSSD and pNN50) and frequency (HF, LF and LF/HF ratio) domains and geometric indices of HRV (RRTri, TINN, SD1, SD2 and SD1/SD2 ratio). The subjects remained at rest for 10 min and then performed the exercises with the flexible poles. Immediately after the exercise protocol, the volunteers remained seated at rest for 60 min and HRV was analyzed.Results: We observed no significant changes in time domain (SDNN: p=0.72; RMSSD: p=0.94 and pNN50: p=0.92) or frequency domain indices (LF [nu]: p=0.98; LF [ms(2)]: p=0.72; HF [nu]: p=0.98; HF [ms(2)]: p=0.82 and LF/HF ratio: p=0.7) or in geometric indices (RRTri: p=0.54; TINN: p=0.77; SD1 p=0.94; SD2: p=0.67 and SD/SD2: p=0.42) before and after a single bout of flexible pole exercise.Conclusion: A single bout of flexible pole exercise did not induce significant changes in cardiac autonomic regulation in healthy women. (C) 2014 Sociedade Portuguesa de Cardiologia. Published by Elsevier Espana, S.L.U. All rights reserved.

Linear and nonlinear measures of fetal heart rate patterns evaluated on very short fetal magnetocardiograms

We analyzed the effectiveness of linear short- and long-term variability time domain parameters, an index of sympatho-vagal balance (SDNN/RMSSD) and entropy in differentiating fetal heart rate patterns (fHRPs) on the fetal heart rate (fHR) series of 5, 3 and 2 min duration reconstructed from 46 fetal magnetocardiograms. Gestational age (GA) varied from 21 to 38 weeks. FHRPs were classified based on the fHR standard deviation. In sleep states, we observed that vagal influence increased with GA, and entropy significantly increased (decreased) with GA (SDNN/RMSSD), demonstrating that a prevalence of vagal activity with autonomous nervous system maturation may be associated with increased sleep state complexity. In active wakefulness, we observed a significant negative (positive) correlation of short-term (long-term) variability parameters with SDNN/RMSSD. ANOVA statistics demonstrated that long-term irregularity and standard deviation of normal-to-normal beat intervals (SDNN) best differentiated among fHRPs. Our results confirm that short-and long-term variability parameters are useful to differentiate between quiet and active states, and that entropy improves the characterization of sleep states. All measures differentiated fHRPs more effectively on very short HR series, as a result of the fMCG high temporal resolution and of the intrinsic timescales of the events that originate the different fHRPs.

Variability in heart rate estimates from different pulse oximeters

Since its introduction, pulse oximetry has become a conventional clinical measure. Besides being arterial blood oxygen saturation (SpO2) measure, pulse oximeters can be used for other cardiovascular measurements, like heart rate (HR) estimations, derived from its photo plethysmographic (PPG) signals. The temporal coherence of the PPG signals and thereby HR estimates are heavily dependent on its minimal phase variability. A Masimo SET Rad-9TM, Novametrix Oxypleth and a custom designed PPG system were investigated for their relative phase variation. R-R intervals from electro-cardiogram (ECG) were recorded concurrently as reference. PPG signals obtained from the 3 systems were evaluated by comparing their respective beat-to-beat (B-B) intervals with the corresponding R-R estimates during a static test. For their relative B-B comparison to the ECG, Novametrix system differed 0.680.52% (p

The role of heart rate as a risk marker for predicting adverse outcomes

Cardiovascular disease is one of the leading causes of death around the world. Resting heart rate has been shown to be a strong and independent risk marker for adverse cardiovascular events and mortality, and yet its role as a predictor of risk is somewhat overlooked in clinical practice. With the aim of highlighting its prognostic value, the role of resting heart rate as a risk marker for death and other adverse outcomes was further examined in a number of different patient populations. A systematic review of studies that previously assessed the prognostic value of resting heart rate for mortality and other adverse cardiovascular outcomes was presented. New analyses of nine clinical trials were carried out. Both the original and extended Cox model that allows for analysis of time-dependent covariates were used to evaluate and compare the predictive value of baseline and time-updated heart rate measurements for adverse outcomes in the CAPRICORN, EUROPA, PROSPER, PERFORM, BEAUTIFUL and SHIFT populations. Pooled individual patient meta-analyses of the CAPRICORN, EPHESUS, OPTIMAAL and VALIANT trials, and the BEAUTIFUL and SHIFT trials, were also performed. The discrimination and calibration of the models applied were evaluated using Harrell’s C-statistic and likelihood ratio tests, respectively. Finally, following on from the systematic review, meta-analyses of the relation between baseline and time-updated heart rate, and the risk of death from any cause and from cardiovascular causes, were conducted. Both elevated baseline and time-updated resting heart rates were found to be associated with an increase in the risk of mortality and other adverse cardiovascular events in all of the populations analysed. In some cases, elevated time-updated heart rate was associated with risk of events where baseline heart rate was not. Time-updated heart rate also contributed additional information about the risk of certain events despite knowledge of baseline heart rate or previous heart rate measurements. The addition of resting heart rate to the models where resting heart rate was found to be associated with risk of outcome improved both discrimination and calibration, and in general, the models including time-updated heart rate along with baseline or the previous heart rate measurement had the highest and similar C-statistics, and thus the greatest discriminative ability. The meta-analyses demonstrated that a 5bpm higher baseline heart rate was associated with a 7.9% and an 8.0% increase in the risk of all-cause and cardiovascular death, respectively (both p less than 0.001). Additionally, a 5bpm higher time-updated heart rate (adjusted for baseline heart rate in eight of the ten studies included in the analyses) was associated with a 12.8% (p less than 0.001) and a 10.9% (p less than 0.001) increase in the risk of all-cause and cardiovascular death, respectively. These findings may motivate health care professionals to routinely assess resting heart rate in order to identify individuals at a higher risk of adverse events. The fact that the addition of time-updated resting heart rate improved the discrimination and calibration of models for certain outcomes, even if only modestly, strengthens the case that it be added to traditional risk models. The findings, however, are of particular importance, and have greater implications for the clinical management of patients with pre-existing disease. An elevated, or increasing heart rate over time could be used as a tool, potentially alongside other established risk scores, to help doctors identify patient deterioration or those at higher risk, who might benefit from more intensive monitoring or treatment re-evaluation. Further exploration of the role of continuous recording of resting heart rate, say, when patients are at home, would be informative. In addition, investigation into the cost-effectiveness and optimal frequency of resting heart rate measurement is required. One of the most vital areas for future research is the definition of an objective cut-off value for the definition of a high resting heart rate.

Robust image hashing using higher order spectral features

Robust image hashing seeks to transform a given input image into a shorter hashed version using a key-dependent non-invertible transform. These image hashes can be used for watermarking, image integrity authentication or image indexing for fast retrieval. This paper introduces a new method of generating image hashes based on extracting Higher Order Spectral features from the Radon projection of an input image. The feature extraction process is non-invertible, non-linear and different hashes can be produced from the same image through the use of random permutations of the input. We show that the transform is robust to typical image transformations such as JPEG compression, noise, scaling, rotation, smoothing and cropping. We evaluate our system using a verification-style framework based on calculating false match, false non-match likelihoods using the publicly available Uncompressed Colour Image database (UCID) of 1320 images. We also compare our results to Swaminathan’s Fourier-Mellin based hashing method with at least 1% EER improvement under noise, scaling and sharpening.