Multivariate system identification for cerebral autoregulation.
The effect of spontaneous beat-to-beat mean arterial blood pressure (ABP) fluctuations and breath-to-breath end-tidal carbon dioxide (PETCO2) and end-tidal oxygen (PETO2) fluctuations on beat-to-beat cerebral bloodflow velocity (CBFV) variations is studied using a multiple coherence function. Multip...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2008
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| _version_ | 1797057822964318208 |
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| author | Peng, T Rowley, AB Ainslie, P Poulin, M Payne, S |
| author_facet | Peng, T Rowley, AB Ainslie, P Poulin, M Payne, S |
| author_sort | Peng, T |
| collection | OXFORD |
| description | The effect of spontaneous beat-to-beat mean arterial blood pressure (ABP) fluctuations and breath-to-breath end-tidal carbon dioxide (PETCO2) and end-tidal oxygen (PETO2) fluctuations on beat-to-beat cerebral bloodflow velocity (CBFV) variations is studied using a multiple coherence function. Multiple coherence is a measure of the extent to which the output, CBFV, can be represented as a linear time invariant system of multiple input signals. Analysis of experimental measurements from 13 different healthy subjects reveal that, with additional inputs, PETCO2 and PETO2, the multiple coherence for frequencies <0.05 Hz is significantly higher than the corresponding values obtained for univariate coherence with a single input of ABP. The result illustrates that the low value of univariate coherence at small frequencies may be due to the effects of PETCO2 and PETO2 fluctuations on CBFV variability. Moreover, it is also found that the transfer function between ABP and CBFVtime series identified from previous univariate techniques at low frequencies can be modified by CO2 and O2 reactivity and no longer represents pressure autoregulation only. Multivariate system identification provides a technique of incorporating additional variability and recovering from this artifact. Finally, a physiologically based model and its linear transfer function are used as a simulation tool to investigate possible causes of low univariate coherence. |
| first_indexed | 2024-03-06T19:41:53Z |
| format | Journal article |
| id | oxford-uuid:20fad100-eded-4fc7-acbc-decd6625fcbb |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:41:53Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | oxford-uuid:20fad100-eded-4fc7-acbc-decd6625fcbb2022-03-26T11:30:34ZMultivariate system identification for cerebral autoregulation.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:20fad100-eded-4fc7-acbc-decd6625fcbbEnglishSymplectic Elements at Oxford2008Peng, TRowley, ABAinslie, PPoulin, MPayne, SThe effect of spontaneous beat-to-beat mean arterial blood pressure (ABP) fluctuations and breath-to-breath end-tidal carbon dioxide (PETCO2) and end-tidal oxygen (PETO2) fluctuations on beat-to-beat cerebral bloodflow velocity (CBFV) variations is studied using a multiple coherence function. Multiple coherence is a measure of the extent to which the output, CBFV, can be represented as a linear time invariant system of multiple input signals. Analysis of experimental measurements from 13 different healthy subjects reveal that, with additional inputs, PETCO2 and PETO2, the multiple coherence for frequencies <0.05 Hz is significantly higher than the corresponding values obtained for univariate coherence with a single input of ABP. The result illustrates that the low value of univariate coherence at small frequencies may be due to the effects of PETCO2 and PETO2 fluctuations on CBFV variability. Moreover, it is also found that the transfer function between ABP and CBFVtime series identified from previous univariate techniques at low frequencies can be modified by CO2 and O2 reactivity and no longer represents pressure autoregulation only. Multivariate system identification provides a technique of incorporating additional variability and recovering from this artifact. Finally, a physiologically based model and its linear transfer function are used as a simulation tool to investigate possible causes of low univariate coherence. |
| spellingShingle | Peng, T Rowley, AB Ainslie, P Poulin, M Payne, S Multivariate system identification for cerebral autoregulation. |
| title | Multivariate system identification for cerebral autoregulation. |
| title_full | Multivariate system identification for cerebral autoregulation. |
| title_fullStr | Multivariate system identification for cerebral autoregulation. |
| title_full_unstemmed | Multivariate system identification for cerebral autoregulation. |
| title_short | Multivariate system identification for cerebral autoregulation. |
| title_sort | multivariate system identification for cerebral autoregulation |
| work_keys_str_mv | AT pengt multivariatesystemidentificationforcerebralautoregulation AT rowleyab multivariatesystemidentificationforcerebralautoregulation AT ainsliep multivariatesystemidentificationforcerebralautoregulation AT poulinm multivariatesystemidentificationforcerebralautoregulation AT paynes multivariatesystemidentificationforcerebralautoregulation |