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Multiscale Complexity Analysis of the Cardiac Control Identifies Asymptomatic and Symptomatic Patients in Long QT Syndrome Type 1  [PDF]
Vlasta Bari, José F. Valencia, Montserrat Vallverdú, Giulia Girardengo, Andrea Marchi, Tito Bassani, Pere Caminal, Sergio Cerutti, Alfred L. George, Paul A. Brink, Lia Crotti, Peter J. Schwartz, Alberto Porta
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0093808
Abstract: The study assesses complexity of the cardiac control directed to the sinus node and to ventricles in long QT syndrome type 1 (LQT1) patients with KCNQ1-A341V mutation. Complexity was assessed via refined multiscale entropy (RMSE) computed over the beat-to-beat variability series of heart period (HP) and QT interval. HP and QT interval were approximated respectively as the temporal distance between two consecutive R-wave peaks and between the R-wave apex and T-wave end. Both measures were automatically taken from 24-hour electrocardiographic Holter traces recorded during daily activities in non mutation carriers (NMCs, n = 14) and mutation carriers (MCs, n = 34) belonging to a South African LQT1 founder population. The MC group was divided into asymptomatic (ASYMP, n = 11) and symptomatic (SYMP, n = 23) patients according to the symptom severity. Analyses were carried out during daytime (DAY, from 2PM to 6PM) and nighttime (NIGHT, from 12PM to 4AM) off and on beta-adrenergic blockade (BBoff and BBon). We found that the complexity of the HP variability at short time scale was under vagal control, being significantly increased during NIGHT and BBon both in ASYMP and SYMP groups, while the complexity of both HP and QT variability at long time scales was under sympathetic control, being smaller during NIGHT and BBon in SYMP subjects. Complexity indexes at long time scales in ASYMP individuals were smaller than those in SYMP ones regardless of therapy (i.e. BBoff or BBon), thus suggesting that a reduced complexity of the sympathetic regulation is protective in ASYMP individuals. RMSE analysis of HP and QT interval variability derived from routine 24-hour electrocardiographic Holter recordings might provide additional insights into the physiology of the cardiac control and might be fruitfully exploited to improve risk stratification in LQT1 population.
On the Significance of Digits in Interval Notation  [PDF]
M. H. van Emden
Computer Science , 2002,
Abstract: To analyse the significance of the digits used for interval bounds, we clarify the philosophical presuppositions of various interval notations. We use information theory to determine the information content of the last digit of the numeral used to denote the interval's bounds. This leads to the notion of efficiency of a decimal digit: the actual value as percentage of the maximal value of its information content. By taking this efficiency into account, many presentations of intervals can be made more readable at the expense of negligible loss of information.
ECG beats classification using waveform similarity and RR interval  [PDF]
Ahmad Khoureich Ka
Physics , 2011,
Abstract: This paper present an electrocardiogram (ECG) beat classification method based on waveform similarity and RR interval. The purpose of the method is to classify six types of heart beats (normal beat, atrial premature beat, paced beat, premature ventricular beat, left bundle branch block beat and right bundle branch block beat). The electrocardiogram signal is first denoised using wavelet transform based techniques. Heart beats of 128 samples data centered on the R peak are extracted from the ECG signal and thence reduced to 16 samples data to constitute a feature. RR intervals surrounding the beat are also exploited as feature. A database of annotated beats is built for the classifier for waveform comparison to unknown beats. Tested on 46 records in the MIT/BIH arrhythmia database, the method shows classification rate of 97.52%.
Discrete Scale Invariance in the Cascade Heart Rate Variability Of Healthy Humans  [PDF]
Der Chyan Lin
Physics , 2004,
Abstract: Evidence of discrete scale invariance (DSI) in daytime healthy heart rate variability (HRV) is presented based on the log-periodic power law scaling of the heart beat interval increment. Our analysis suggests multiple DSI groups and a dynamic cascading process. A cascade model is presented to simulate such a property.
Correlations between the Signal Complexity of Cerebral and Cardiac Electrical Activity: A Multiscale Entropy Analysis  [PDF]
Pei-Feng Lin, Men-Tzung Lo, Jenho Tsao, Yi-Chung Chang, Chen Lin, Yi-Lwun Ho
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0087798
Abstract: The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1–58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11–20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6–20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration.
Beat-to-Beat Vectorcardiographic Analysis of Ventricular Depolarization and Repolarization in Myocardial Infarction  [PDF]
Muhammad A. Hasan, Derek Abbott, Mathias Baumert
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0049489
Abstract: Objectives Increased beat-to-beat variability in the QT interval has been associated with heart disease and mortality. The purpose of this study was to investigate the beat-to-beat spatial and temporal variations of ventricular depolarization and repolarization in vectorcardiogram (VCG) for characterising myocardial infarction (MI) patients. Methods Standard 12-lead ECGs of 84 MI patients (22 f, 63±12 yrs; 62 m, 56±10 yrs) and 69 healthy subjects (17 f, 42±18 yrs; 52 m, 40±13 yrs) were investigated. To extract the beat-to-beat QT intervals, a template-matching algorithm and the singular value decomposition method have been applied to synthesise the ECG data to VCG. Spatial and temporal variations in the QRS complex and T-wave loops were studied by investigating several descriptors (point-to-point distance variability, mean loop length, T-wave morphology dispersion, percentage of loop area, total cosine R-to-T). Results Point-to-point distance variability of QRS and T-loops (0.13±0.04 vs. 0.10±0.04, p< 0.0001 and 0.16±0.07 vs. 0.13±0.06, p< 0.05) were significantly larger in the MI group than in the control group. The average T-wave morphology dispersion was significantly higher in the MI group than in the control group (62°±8° vs. 38°±16°, p< 0.0001). Further, its beat-to-beat variability appeared significantly lower in the MI group than in the control group (12°±5° vs. 15°±6°, p< 0.005). Moreover, the average percentage of the T-loop area was found significantly lower in the MI group than the controls (46±17 vs. 55±15, p< 0.001). Finally, the average and beat-to-beat variability of total cosine R-to-T were not found statistically significant between both groups. Conclusions Beat-to-beat assessment of VCG parameters may have diagnostic attributes that might help in identifying MI patients.
DETERMINATION OF THE DISTANCE BETWEEN TWO ADJACENT STATIONS, THE OBSERVATIONAL VERTICAL INCREMENT AND THE OBSERVATIONAL TIME INTERVAL IN OPTIMUM SENSE

Liao Dongxian,

大气科学进展 , 1985,
Abstract: Considering the observational error, the truncation error and the requirements of numerical weather prediction, three formulas for determining the distance between two adjacent stationsd 1, the observational vertical increment Δp 1 and the observational time interval Δt 1 in optimum sense, have been derived. Since they depend on the shortest wavelength concerned and the ratio of maximum observational error to wave amplitude, the results are quite different for different scale systems. For the filtered model the values ofd 1, Δp 1, and Δt 1 general come near those required in the MANUAL on the GOS published in 1980 by WMO. But for the primitive equation model the estimated value of Δt 1 is much less than those required in the filtered model case. Therefore, it is improper to study the fast moving and developing processes of the atmospheric motion only on the basis of the conventional observations. It seems to be necessary to establish an optimum composite observational system including the surface-based system and the space-based system.
Modeling Pharmacological Clock and Memory Patterns of Interval Timing in a Striatal Beat-Frequency Model with Realistic, Noisy Neurons  [PDF]
Sorinel A. Oprisan,Catalin V. Buhusi
Frontiers in Integrative Neuroscience , 2011, DOI: 10.3389/fnint.2011.00052
Abstract: In most species, the capability of perceiving and using the passage of time in the seconds-to-minutes range (interval timing) is not only accurate but also scalar: errors in time estimation are linearly related to the estimated duration. The ubiquity of scalar timing extends over behavioral, lesion, and pharmacological manipulations. For example, in mammals, dopaminergic drugs induce an immediate, scalar change in the perceived time (clock pattern), whereas cholinergic drugs induce a gradual, scalar change in perceived time (memory pattern). How do these properties emerge from unreliable, noisy neurons firing in the milliseconds range? Neurobiological information relative to the brain circuits involved in interval timing provide support for an striatal beat frequency (SBF) model, in which time is coded by the coincidental activation of striatal spiny neurons by cortical neural oscillators. While biologically plausible, the impracticality of perfect oscillators, or their lack thereof, questions this mechanism in a brain with noisy neurons. We explored the computational mechanisms required for the clock and memory patterns in an SBF model with biophysically realistic and noisy Morris–Lecar neurons (SBF–ML). Under the assumption that dopaminergic drugs modulate the firing frequency of cortical oscillators, and that cholinergic drugs modulate the memory representation of the criterion time, we show that our SBF–ML model can reproduce the pharmacological clock and memory patterns observed in the literature. Numerical results also indicate that parameter variability (noise) – which is ubiquitous in the form of small fluctuations in the intrinsic frequencies of neural oscillators within and between trials, and in the errors in recording/retrieving stored information related to criterion time – seems to be critical for the time-scale invariance of the clock and memory patterns.
Multiscale entropy (MSE) and multicomponent complexity (MCC)  [cached]
M. Boorboor,F. shahbazi,B. Mirza
Iranian Journal of Physics Research , 2007,
Abstract: Multiscale entropy (MSE) is a powerful method for determining the complexity of random time series. In this paper we, investigate the cardiac heart interbeat interval (RR) time series by introducing a new method based on MSE, called multicomponent complexity (MCC) and find clear difference between healthy samples and samples with Congestive heart failure (CHF) disease.
Heart Rate and QT interval Variability in Multiple Sclerosis: Evidence for Decreased Sympathetic Activity  [PDF]
Micahel BONNETT,Janet MULCARE,Thomas MATHEWS,Satyendra GUPTA
Journal of Neurological Sciences , 2006,
Abstract: Decreased beat-to-beat heart rate variability (HR) and increased beat-to-beat QT interval variability are associated with significant cardiovascular mortality. The aim of this study was to compare beat-to-beat HR and QT variability among patients with multiple sclerosis (MS) and normal controls to investigate cardiac autonomic function. We investigated spectral measures of HR and QT interval variability in 13 patients with MS and 16 normal controls during sleep. Our results showed modest but significant decreases in HR total power (TP: 0-0.5 Hz), VLF power (very low frequency power: 0-0.04 Hz) and LF power (low frequency: 0.14-0.5 Hz) in patients with MS compared to normal controls. QT interval TP, VLF, LF and HF powers were all highly significantly lower (p<0.00001) in MS patients compared to normal controls. QTvi, a normalized index of QT variability corrected for mean QT interval divided by heart rate variability corrected for mean heart rate was significantly lower in MS patients. There was a significant inverse correlation between fatigue scores and QT TP, VLF and LF powers (p=0.03 to 0.01). These findings suggest a decrease in cardiac sympathetic function more than a decrease in vagal function in some patients with multiple sclerosis, and decreased sympathetic function may be related to fatigue in these patients.
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