Spectral and symbolic analysis of heart rate data during the tilt test

Cammarota, Camillo; Rogora, Enrico

doi:10.1103/physreve.74.042903

Cited by 13 publications

(9 citation statements)

References 9 publications

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“…the patterns show a considerable amount of successive 0s or 1s [17]. The binary patterns are also capable of reflecting changes of the cardiac autonomic regulation during head-up tilt [18,19] and during childhood and adolescence [20]. The occurrence of regular binary patterns is linked to sympathetic modulations, whereas the occurrence of irregular binary patterns is linked to parasympathetic modulations.…”

Section: Introductionmentioning

confidence: 98%

Strategies of symbolization in cardiovascular time series to test individual gestational development in the fetus

Cysarz

Edelhäuser

Leeuwen

2015

Phil. Trans. R. Soc. A.

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The analysis of symbolic dynamics applied to physiological time series retrieves dynamical properties of the underlying regulation which are robust against the symbolic transformation. In this study, three different transformations to produce a symbolic series were applied to fetal RR interval series to test whether they reflect individual changes of fetal heart rate variability in the course of pregnancy. Each transformation was applied to 215 heartbeat datasets obtained from 11 fetuses during the second and the third trimester of pregnancy (at least 10 datasets per fetus, median 17). In the symbolic series, the occurrence of symbolic sequences of length 3 was categorized according to the amount of variations in the sequence: no variation of the symbols, one variation, two variations. Linear regression with respect to gestational age showed that the individual course during pregnancy performed best using a binary transformation reflecting whether the RR interval differences are below or above a threshold. The median goodness of fit of the individual regression lines was 0.73 and also the variability among the individual slopes was low. Other transformations to symbolic dynamics performed worse but were still able to reflect the individual progress of fetal cardiovascular regulation.

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Section: Introductionmentioning

confidence: 98%

Strategies of symbolization in cardiovascular time series to test individual gestational development in the fetus

Cysarz

Edelhäuser

Leeuwen

2015

Phil. Trans. R. Soc. A.

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“…Biological systems usually consist of several subsystems which are interrelated by feedbacks with time delay. To reveal such time-delayed coupling directions from biosignals is a basic task in understanding such systems [1][2][3][4][5][6][7][8]. Data recorded from these systems reflect biological activities of living beings and are characterized on the one hand by real biological information, including nonstationarities, nonlinearities and intrinsic noise, and on the other hand by measurement noise.…”

mentioning

confidence: 99%

Detection of time-delayed interactions in biosignals using symbolic coupling traces

et al. 2009

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Directional coupling analysis of bivariate time series is an important subject of current research. In this letter, a method based on symbolic dynamics for the detection of time-delayed coupling is presented. The symbolic coupling traces, defined as the symmetric and diametric traces of the bivariate word distribution, allow for the quantification of coupling and are compared with established methods like mutual information and cross recurrence analysis. The symbolic coupling traces method is applied to model systems and cardiological data which demonstrate its advantages especially for nonstationary data.

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“…patterns with a low number of changes between 0s and 1s [14]. Furthermore, these patterns are also capable of reflecting changes of the cardiac autonomic regulation during head-up tilt [15,16]. The occurrence of regular binary patterns is linked to sympathetic modulations whereas the occurrence of irregular binary patterns is linked to parasympathetic modulations.…”

Section: Introductionmentioning

confidence: 99%

Different approaches of symbolic dynamics to quantify heart rate complexity

Cysarz

Porta

Montano

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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The analysis of symbolic dynamics applied to physiological time series is able to retrieve information about dynamical properties of the underlying system that cannot be gained with standard methods like e.g. spectral analysis. Different approaches for the transformation of the original time series to the symbolic time series have been proposed. Yet the differences between the approaches are unknown. In this study three different transformation methods are investigated: (1) symbolization according to the deviation from the average time series, (2) symbolization according to several equidistant levels between the minimum and maximum of the time series, (3) binary symbolization of the first derivative of the time series. Each method was applied to the cardiac interbeat interval series RR(i) and its difference ΔRR(I) of 17 healthy subjects obtained during head-up tilt testing. The symbolic dynamics of each method is analyzed by means of the occurrence of short sequences ('words') of length 3. The occurrence of words is grouped according to words without variations of the symbols (0V%), words with one variation (1V%), two like variations (2LV%) and two unlike variations (2UV%). Linear regression analysis showed that for method 1 0V%, 1V%, 2LV% and 2UV% changed with increasing tilt angle. For method 2 0V%, 2LV% and 2UV% changed with increasing tilt angle and method 3 showed changes for 0V% and 1V%. In conclusion, all methods are capable of reflecting changes of the cardiac autonomic nervous system during head-up tilt. All methods show that even the analysis of very short symbolic sequences is capable of tracking changes of the cardiac autonomic regulation during head-up tilt testing.

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Spectral and symbolic analysis of heart rate data during the tilt test

Cited by 13 publications

References 9 publications

Strategies of symbolization in cardiovascular time series to test individual gestational development in the fetus

Strategies of symbolization in cardiovascular time series to test individual gestational development in the fetus

Detection of time-delayed interactions in biosignals using symbolic coupling traces

Different approaches of symbolic dynamics to quantify heart rate complexity

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