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total: 9
Search results for: PERMUTATION ENTROPY
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The values of Permutation Entropy for individuals with Normal Sinus Rhythm
Open Research DataThe dataset consists of calculated values of entropy of 75 000 intervals between consecutive heartbeats (RR intervals) for 54 patients with normal sinus rhythm (NSR). The original data were taken from PhysioNet Normal Sinus Rhythm RR Interval Database (cf. Goldberger A., Amaral L., Glass L., Hausdorff J., Ivanov P.C., Mark R., Mietus J.E., Moody G.B.,...
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The values of Permutation Entropy for patients with Congestive Heart Failure
Open Research DataThe dataset consists of calculated values of entropy of 75 000 intervals between consecutive heartbeats (RR intervals) for 29 patients with congestive heart failure (CHF). The original data were taken from PhysioNet Congestive Heart Failure RR Interval Database (cf. Goldberger A., Amaral L., Glass L., Hausdorff J., Ivanov P.C., Mark R., Mietus J.E.,...
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APPLICATION OF ENTROPY-BASED METHODS TO DISTINGUISH HEALTHY INDIVIDUALS WITH NORMAL SINUS RHYTHM FROM PATIENTS WITH CONGESTIVE HEART FAILURE
PublicationIn this paper, we examined whether entropy-based methods are able to differentiate healthy individuals from patients with congestive heart failure. To this aim, we applied two methods: Permutation Entropy and Block Entropy. Long-term ECG recordings (75 000 RR intervals) were analyzed. The results proved that both methods can distinguish those groups on condition that the parameters are appropriately chosen.
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Entropy Measures of heart rate variability for short ECG datasets in patients with congestive heart failure
PublicationWe investigated the usefulness of entropy measures calculated for short ECG series in distinguishing healthy subjects from patients with congestive heart failure (CHF). Four entropy measures were tested: Approximate Entropy (ApEn), Sample Entropy (SampEn), Fuzzy Entropy (Fuzzy En) and Permutation Entropy (PE), each computed for ECG series of 1000, 500, 250 and 100 RR intervals. We found that with a reduction of the data set length...
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Entropy measures of heart rate variability for short ECG datasets in patients with congestive heart failure
PublicationWe investigated the usefulness of entropy measures calculated for short ECG series in distinguishing healthy subjects from patients with congestive heart failure (CHF). Four entropy measures were tested: Approximate Entropy (ApEn), Sample Entropy (SampEn), Fuzzy Entropy (FuzzyEn) and Permutation Entropy (PE), each computed for ECG series of 1000, 500, 250 and 100 RR intervals. We found that with a reduction of the data set length...
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Entropic Measures of Complexity of Short-Term Dynamics of Nocturnal Heartbeats in an Aging Population
PublicationTwo entropy-based approaches are investigated to study patterns describing differences in time intervals between consecutive heartbeats. The first method explores matrices arising from networks of transitions constructed following events represented by a time series. The second method considers distributions of ordinal patterns of length three, whereby patterns with repeated values are counted as different patterns. Both methods provide...
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Entropy Measures in the Assessment of Heart Rate Variability in Patients with Cardiodepressive Vasovagal Syncope
PublicationSample entropy (SampEn) was reported to be useful in the assessment of the complexity of heart rate dynamics. Permutation entropy (PermEn) is a new measure based on the concept of order and was previously shown to be accurate for short, non-stationary datasets. The aim of the present study is to assess if SampEn and PermEn obtained from baseline recordings might differentiate patients with various outcomes of the head-up tilt test...
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Cross-validation for triplets of HRV and BPV indices based on ordinal patterns in differentiating OSA patients from healthy controls
Open Research DataResults of cross-validation for triplets of HRV and BPV indices based on ordinal patterns, as described in the paper “Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate–blood pressure coupling quantified by entropy-based indices” by P. Pilarczyk, G. Graff, J.M. Amigó, K. Tessmer, K. Narkiewicz, B. Graff.
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HRV and BPV indices in differentiating OSA patients from healthy controls
Open Research DataThe various HRV and BPV indices computed for the purpose of the analyses described in the paper “Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate–blood pressure coupling quantified by entropy-based indices” by P. Pilarczyk, G. Graff, J.M. Amigó, K. Tessmer, K. Narkiewicz, and B. Graff.