ON CHAOS DETECTION METHODS

1996 ◽  
Vol 06 (03) ◽  
pp. 529-543 ◽  
Author(s):  
KARIN VIBE ◽  
JEAN-MARC VESIN

Reliable chaos detection in real-world time series is attracting increasing attention in the scientific community. This work shows that it is possible to use chaos analysis methods such as attractor dimension estimation, Lyapunov exponents estimation and nonlinear prediction, under the condition that the limitations and drawbacks of the algorithms used are kept in mind. Three existing algorithms for chaos characterization are analyzed in terms of classification performances and robustness with respect to noise and data length. It is shown that all three help detect chaos and even classify different types of signals, but that their results are not devoid of ambiguity. An illustrative example is given, in which the algorithms presented are applied to heart rate variability signals, and directions of research are proposed for the design of a straightforward and simple chaos detection methodology.

1998 ◽  
Vol 274 (6) ◽  
pp. H1970-H1978 ◽  
Author(s):  
Daniel E. Roach ◽  
Robert S. Sheldon

Many chaos detection methods have proven inherently ambiguous in that they yield similar results for chaotic signals and correlated noise. The purpose of this work was to determine whether human resting heart period sequences have global properties characteristic of chaotic systems. We investigated the inherent global organization of heart period sequences by quantifying how the information content of the embedded sequences varied as a function of scale. We compared the information scaling characteristics of 60-min heart period sequences obtained from 10 healthy resting volunteers with those obtained from numerous periodic and chaotic control sequences. The information scaling properties of the heart period sequences were significantly different from those obtained for the controls, particularly at the coarsest scales ( P = 0.0003 vs. low-dimensional periodic controls; P = 0.0005 vs. low-dimensional chaotic controls; P = 0.0003 vs. low-dimensional periodic and chaotic controls). We also showed that nondeterministic components, such as large tachycardic (or bradycardic) events or aperiodic fluctuations, can lead to scaling characteristics similar to those observed for the resting heart period sequences. This, in addition to previous evidence from spectral, nonlinear predictability and lexical studies, favors an events-based approach to understanding heart rate variability.


1995 ◽  
Vol 269 (2) ◽  
pp. H480-H486 ◽  
Author(s):  
Y. Yamamoto ◽  
J. O. Fortrat ◽  
R. L. Hughson

The purpose of the present study was to investigate the basic fractal nature of the variability in resting heart rate (HRV), relative to that in breathing frequency (BFV) and tidal volume (TVV), and to test the hypothesis that fractal HRV is due to the fractal BFV and/or TVV in humans. In addition, the possible fractal nature of respiratory volume curves (RVC) and HRV was observed. In the first study, eight subjects were tested while they sat quietly in a comfortable chair for 60 min. Beat-to-beat R-R intervals, i.e., HRV, and breath-by-breath BFV and TVV were measured. In the second study, six subjects were tested while they were in the supine position for 20-30 min. The RVC was monitored continuously together with HRV. Coarse-graining spectral analysis (Yamamoto, Y., and R. L. Hughson, Physica D 68: 250-264, 1993) was applied to these signals to evaluate the percentage of random fractal components in the time series (%Fractal) and the spectral exponent (beta), which characterizes irregularity of the signals. The estimates of beta were determined for each variable only over the range normally used to evaluate HRV. Values for %Fractal and beta of both BFV and TVV were significantly (P < 0.05) greater than those for HRV. In addition, there was no significant (P > 0.05) correlation between the beta values of HRV relative to either BFV (r = 0.14) or TVV (r = 0.34). RVC showed a smooth oscillation as compared with HRV; %Fractal for RVC (42.3 +/- 21.7%, mean +/- SD) was significantly (P < 0.05) lower than that for HRV (78.5 +/- 4.2%).(ABSTRACT TRUNCATED AT 250 WORDS)


2013 ◽  
Vol 111 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Miguel A. García-González ◽  
Mireya Fernández-Chimeno ◽  
Lluis Capdevila ◽  
Eva Parrado ◽  
Juan Ramos-Castro

2021 ◽  
Vol 6 (5) ◽  
pp. 456-464
Author(s):  
A. P. Romanchuk ◽  
◽  
O. V. Guzii ◽  
A. V. Maglyovanyi ◽  
◽  
...  

The purpose of the study was a comparative analysis of sensorimotor reactions in highly trained athletes with different types of heart rate regulation. Materials and methods. 202 highly trained male athletes aged 22.6±2.8 years, who are engaged in acyclic sports – martial arts (karate, taekwondo, kickboxing, boxing, freestyle wrestling, Greco-Roman wrestling, judo, sambo) and games (water polo, soccer) were examined. The experience in sports was 10.3±3.1 years. All studies were conducted in the pre-competition period in the morning. Based on the study of heart rate variability in athletes, the type of heart rate regulation was determined. The basis for determining the types of regulation is the classification of heart rate variability indicators, taking into account their inclusion in certain limits. Heart rate variability indicators that reflect the dual-circuit model of heart rate regulation and are used for diagnosis include: total heart rate variability – total power (ms2), very low frequency (ms2), and stress-index (e.u.), which reflect the various chains of regulatory effects on heart rate. According to certain data types, 4 groups were formed. 1 group (type I) consisted of 42 athletes, 2 (type II) – 28 athletes, 3 (type III) – 88 athletes, 4 (type IV) – 44 athletes. The study of sensorimotor function was performed using the device KMM-3. Results and discussion. It is shown that the most balanced sensorimotor reactions are in athletes with type III regulation of heart rate. The most strain sensorimotor reactions are observed in type II regulation of heart rate, which is reflected in the pronounced central asymmetry of movement control with acceleration to the left against the background of deteriorating accuracy of right (due to flexors) and left (due to extensors) limbs, and the right-hand predominance. Sensorimotor reactions are quite strain in type IV of heart rate regulation, which is characterized by slow reactions at the synaptic and peripheral levels. In type I of heart rate regulation, the disorders observed at the central level of regulation relate to the asymmetry of short-term motor memory processes, which are significantly reduced in the left hemisphere. Conclusion. The study shows that the differences in the regulatory support of heart rate in highly qualified athletes are accompanied by characteristic differences in sensorimotor function. The latter can be useful for the diagnosis and further correction of conditions associated with the development of overexertion and overtraining


Engineering ◽  
2013 ◽  
Vol 05 (10) ◽  
pp. 310-313
Author(s):  
Ping Shi ◽  
Youfang Fang ◽  
Hongliu Yu

2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Da Un Jeong ◽  
Getu Tadele Taye ◽  
Han-Jeong Hwang ◽  
Ki Moo Lim

Ventricular fibrillation (VF) is a cardiovascular disease that is one of the major causes of mortality worldwide, according to the World Health Organization. Heart rate variability (HRV) is a biomarker that is used for detecting and predicting life-threatening arrhythmias. Predicting the occurrence of VF in advance is important for saving patients from sudden death. We extracted features from seven HRV data lengths to predict the onset of VF before nine different forecast times and observed the prediction accuracies. By using only five features, an artificial neural network classifier was trained and validated based on 10-fold cross-validation. Maximum prediction accuracies of 88.18% and 88.64% were observed at HRV data lengths of 10 and 20 s, respectively, at a forecast time of 0 s. The worst prediction accuracy was recorded at an HRV data length of 70 s and a forecast time of 80 s. Our results showed that features extracted from HRV signals near the VF onset could yield relatively high VF prediction accuracies.


1998 ◽  
Vol 13 (5) ◽  
pp. 252-265 ◽  
Author(s):  
Brahm Goldstein ◽  
Timothy G. Buchman

Clinicians have long been aware that the normal oscillations in a heart beat are lost during fetal distress, during the early stages of heart failure, with advanced aging, and with critical illness and injury. However, these oscillations, or variability in heart rate and other cardiovascular signals, have largely been ignored or discounted as variances from the mean or average values. It is becoming increasingly clear that these oscillations reflect the dynamic interactions of many physiologic processes, including neuroautonomic regulation of heart rate and blood pressure. We present a synthesis and review of the current literature concerning heart rate variability with special reference to intensive care. This article describes the background of time series analysis of heart rate variability including time and frequency domain and nonlinear measurements. The implications and potential for time series analysis of variability in cardiovascular signals in clinical diagnosis and management of critically ill and injured patients are discussed.


2006 ◽  
Vol 195 (6) ◽  
pp. S230
Author(s):  
Rathinaswamy Govindan ◽  
Eric Siegel ◽  
James Wilson ◽  
Hari Eswaran ◽  
Hubert Preissl ◽  
...  

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