Copula as a dynamic measure of cardiovascular signal interactions
2018
Аутори
Jovanović, SlađanaSkorić, Tamara
Sarenac, Olivera
Milutinović-Smiljanić, Sanja
Japundžić-Žigon, Nina
Bajić, Dragana
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
Objectives: Copula is a tool for measuring linear and non-linear interactions between two or more time series. The aim of this paper is to prove that a copula approach can accurately capture and visualize the spatial and temporal fluctuations in dependency structures of cardiovascular signals, and to outline the application possibilities. Methods: The method for measuring the level of interaction between systolic blood pressure and the corresponding pulse interval is validated statistically and pharmacologically. The time series are recorded from the freely moving male Wistar rats equipped with radio-telemetry device for blood pressure recording, before and after administration of autonomic blockers scopolamine, atenolol, prazosin and hexamethonium. Implicit (Gaussian and t) and explicit (Clayton, Frank and Gumbel) copulas were calculated and compared to the conventional bivariate methods (Kendal, Pearson, Spearman and classical correlation). Further statistical validation was done usi...ng artificially generated surrogate data. A window sliding procedure for dynamic monitoring the signals' coupling strength is implemented. Results: Under the baseline physiological conditions, SBP-PI dependency is significant for time lags 0 s-4 s. Hexamethonium completely abolished the dependency, scopolamine abolished it for time lags 0 s-2 s, atenolol first slightly increased, than for lags greater than 2 s decreased the dependency and prazosin had no effect. Isospectral and isodistributional surrogate data tests confirm that copulas successfully notify the absence of dependency as well. Conclusion: Copula approach accurately captures the temporal fluctuations in dependency structures of SBP and PI, simultaneously enabling a visualization of dependency levels within the particular signal zones. An analysis showed that copulas are more sensitive than the conventional statistical measures, with Frank copula exhibiting the best characterization of SBP and PI dependency.
Кључне речи:
Copula / Systolic blood pressure / Pulse interval / Pharmacological blockade / Dynamic multivariate dependency / Time lagИзвор:
Biomedical Signal Processing & Control, 2018, 43, 250-264Издавач:
- Elsevier Sci Ltd, Oxford
Финансирање / пројекти:
- Развој мултиваријабилних метода за аналитичку подршку биомедицинској дијагностици (RS-MESTD-Technological Development (TD or TR)-32040)
- Telekom Serbia
- Функционална геномика хипоталамуса и медуле у хипертензији индукованој хроничним стресом (RS-MESTD-Integrated and Interdisciplinary Research (IIR or III)-41013)
DOI: 10.1016/j.bspc.2018.03.007
ISSN: 1746-8094
WoS: 000432508100023
Scopus: 2-s2.0-85044663429
Колекције
Институција/група
Stomatološki fakultetTY - JOUR AU - Jovanović, Slađana AU - Skorić, Tamara AU - Sarenac, Olivera AU - Milutinović-Smiljanić, Sanja AU - Japundžić-Žigon, Nina AU - Bajić, Dragana PY - 2018 UR - https://smile.stomf.bg.ac.rs/handle/123456789/2291 AB - Objectives: Copula is a tool for measuring linear and non-linear interactions between two or more time series. The aim of this paper is to prove that a copula approach can accurately capture and visualize the spatial and temporal fluctuations in dependency structures of cardiovascular signals, and to outline the application possibilities. Methods: The method for measuring the level of interaction between systolic blood pressure and the corresponding pulse interval is validated statistically and pharmacologically. The time series are recorded from the freely moving male Wistar rats equipped with radio-telemetry device for blood pressure recording, before and after administration of autonomic blockers scopolamine, atenolol, prazosin and hexamethonium. Implicit (Gaussian and t) and explicit (Clayton, Frank and Gumbel) copulas were calculated and compared to the conventional bivariate methods (Kendal, Pearson, Spearman and classical correlation). Further statistical validation was done using artificially generated surrogate data. A window sliding procedure for dynamic monitoring the signals' coupling strength is implemented. Results: Under the baseline physiological conditions, SBP-PI dependency is significant for time lags 0 s-4 s. Hexamethonium completely abolished the dependency, scopolamine abolished it for time lags 0 s-2 s, atenolol first slightly increased, than for lags greater than 2 s decreased the dependency and prazosin had no effect. Isospectral and isodistributional surrogate data tests confirm that copulas successfully notify the absence of dependency as well. Conclusion: Copula approach accurately captures the temporal fluctuations in dependency structures of SBP and PI, simultaneously enabling a visualization of dependency levels within the particular signal zones. An analysis showed that copulas are more sensitive than the conventional statistical measures, with Frank copula exhibiting the best characterization of SBP and PI dependency. PB - Elsevier Sci Ltd, Oxford T2 - Biomedical Signal Processing & Control T1 - Copula as a dynamic measure of cardiovascular signal interactions VL - 43 SP - 250 EP - 264 DO - 10.1016/j.bspc.2018.03.007 ER -
@article{ author = "Jovanović, Slađana and Skorić, Tamara and Sarenac, Olivera and Milutinović-Smiljanić, Sanja and Japundžić-Žigon, Nina and Bajić, Dragana", year = "2018", abstract = "Objectives: Copula is a tool for measuring linear and non-linear interactions between two or more time series. The aim of this paper is to prove that a copula approach can accurately capture and visualize the spatial and temporal fluctuations in dependency structures of cardiovascular signals, and to outline the application possibilities. Methods: The method for measuring the level of interaction between systolic blood pressure and the corresponding pulse interval is validated statistically and pharmacologically. The time series are recorded from the freely moving male Wistar rats equipped with radio-telemetry device for blood pressure recording, before and after administration of autonomic blockers scopolamine, atenolol, prazosin and hexamethonium. Implicit (Gaussian and t) and explicit (Clayton, Frank and Gumbel) copulas were calculated and compared to the conventional bivariate methods (Kendal, Pearson, Spearman and classical correlation). Further statistical validation was done using artificially generated surrogate data. A window sliding procedure for dynamic monitoring the signals' coupling strength is implemented. Results: Under the baseline physiological conditions, SBP-PI dependency is significant for time lags 0 s-4 s. Hexamethonium completely abolished the dependency, scopolamine abolished it for time lags 0 s-2 s, atenolol first slightly increased, than for lags greater than 2 s decreased the dependency and prazosin had no effect. Isospectral and isodistributional surrogate data tests confirm that copulas successfully notify the absence of dependency as well. Conclusion: Copula approach accurately captures the temporal fluctuations in dependency structures of SBP and PI, simultaneously enabling a visualization of dependency levels within the particular signal zones. An analysis showed that copulas are more sensitive than the conventional statistical measures, with Frank copula exhibiting the best characterization of SBP and PI dependency.", publisher = "Elsevier Sci Ltd, Oxford", journal = "Biomedical Signal Processing & Control", title = "Copula as a dynamic measure of cardiovascular signal interactions", volume = "43", pages = "250-264", doi = "10.1016/j.bspc.2018.03.007" }
Jovanović, S., Skorić, T., Sarenac, O., Milutinović-Smiljanić, S., Japundžić-Žigon, N.,& Bajić, D.. (2018). Copula as a dynamic measure of cardiovascular signal interactions. in Biomedical Signal Processing & Control Elsevier Sci Ltd, Oxford., 43, 250-264. https://doi.org/10.1016/j.bspc.2018.03.007
Jovanović S, Skorić T, Sarenac O, Milutinović-Smiljanić S, Japundžić-Žigon N, Bajić D. Copula as a dynamic measure of cardiovascular signal interactions. in Biomedical Signal Processing & Control. 2018;43:250-264. doi:10.1016/j.bspc.2018.03.007 .
Jovanović, Slađana, Skorić, Tamara, Sarenac, Olivera, Milutinović-Smiljanić, Sanja, Japundžić-Žigon, Nina, Bajić, Dragana, "Copula as a dynamic measure of cardiovascular signal interactions" in Biomedical Signal Processing & Control, 43 (2018):250-264, https://doi.org/10.1016/j.bspc.2018.03.007 . .