Med Biol Eng Comput - Testing pattern synchronization in coupled systems through different entropy-based measures.

Tópicos

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Resumo

Pattern synchronization (PS) can capture one aspect of the dynamic interactions between bivariate physiological systems. It can be tested by several entropy-based measures, e.g., cross sample entropy (X-SampEn), cross fuzzy entropy (X-FuzzyEn), multivariate multiscale entropy (MMSE), etc. A comprehensive comparison on their distinguishability is currently missing. Besides, they are highly dependent on several pre-defined parameters, the threshold value r in particular. Thus, their consistency also needs further elucidation. Based on the well-accepted assumption that a tight coupling necessarily leads to a high PS, we performed a couple of evaluations over several simulated coupled models in this study. All measures were compared to each other with respect to their consistency and distinguishability, which were quantified by two pre-defined criteria-degree of crossing (DoC) and degree of monotonicity (DoM). Results indicated that X-SampEn and X-FuzzyEn could only work well over coupled stochastic systems with meticulously selected r. It is thus not recommended to apply them to the intrinsic complex physiological systems. However, MMSE was suitable for both, indicating by relatively higher DoC and DoM values. Final analysis on the cardiorespiratory coupling validated our results.

Resumo Limpo

pattern synchron ps can captur one aspect dynam interact bivari physiolog system can test sever entropybas measur eg cross sampl entropi xsampen cross fuzzi entropi xfuzzyen multivari multiscal entropi mmse etc comprehens comparison distinguish current miss besid high depend sever predefin paramet threshold valu r particular thus consist also need elucid base wellaccept assumpt tight coupl necessarili lead high ps perform coupl evalu sever simul coupl model studi measur compar respect consist distinguish quantifi two predefin criteriadegre cross doc degre monoton dom result indic xsampen xfuzzyen work well coupl stochast system meticul select r thus recommend appli intrins complex physiolog system howev mmse suitabl indic relat higher doc dom valu final analysi cardiorespiratori coupl valid result

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