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Authors: Natalia Angarita Jaimes and David Simpson

Affiliation: University of Southampton, United Kingdom

Keyword(s): Cerebral Autoregulation, Linear and Non-linear system identification, Blood flow, Blood pressure, Physiological modeling, Volterra-Wiener models, Wiener-Laguerre models.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Cardiovascular Signals ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing ; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics

Abstract: Autoregulation mechanisms maintain blood flow approximately stable despite changes in arterial blood pressure. Mathematical models that characterize this system have been used in the quantitative assessment of function/impairment of autoregulation as well as in furthering the understanding of cerebral hemodynamics. Using spontaneous fluctuations in arterial blood pressure (ABP) as input and cerebral blood flow velocity (CBFV) as output, the autoregulatory mechanism has been modeled using linear and nonlinear approaches. From these models, a small number of measures have been extracted to provide an overall assessment of autoregulation. Previous studies have considered a single – or at most- a couple of measures, making it difficult to compare the performance of different autoregulatory parameters (and the different modeling approaches) under similar conditions. We therefore compare the performance of established autoregulatory parameters in addition to novel features extracted from t he models’ response to a band-pass filtered impulse. We investigate if some of the poor performance previously reported can be overcome by a better choice of autoregulation parameter to extract from the model. Twenty-six recordings of ABP and CBFV from normocapnia and hypercapnia in 13 healthy adults were analyzed. In the absence of a ‘gold’ standard for the study of dynamic cerebral autoregulation, lower inter and intra subject variability of the parameters and better separation between normo- and hyper-capnia states were considered as criteria for identifying improved measures of autoregulation. We found that inter- and intra- subject variability in the assessment of autoregulation can be significantly improved by a careful choice of autoregulation measure extracted from either linear or non-linear models. (More)

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Paper citation in several formats:
Angarita Jaimes, N. and Simpson, D. (2011). OPTIMIZING THE ASSESSMENT OF CEREBRAL AUTOREGULATION FROM LINEAR AND NONLINEAR MODELS . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2011) - BIOSIGNALS; ISBN 978-989-8425-35-5; ISSN 2184-4305, SciTePress, pages 251-256. DOI: 10.5220/0003164902510256

@conference{biosignals11,
author={Natalia {Angarita Jaimes}. and David Simpson.},
title={OPTIMIZING THE ASSESSMENT OF CEREBRAL AUTOREGULATION FROM LINEAR AND NONLINEAR MODELS },
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2011) - BIOSIGNALS},
year={2011},
pages={251-256},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003164902510256},
isbn={978-989-8425-35-5},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2011) - BIOSIGNALS
TI - OPTIMIZING THE ASSESSMENT OF CEREBRAL AUTOREGULATION FROM LINEAR AND NONLINEAR MODELS
SN - 978-989-8425-35-5
IS - 2184-4305
AU - Angarita Jaimes, N.
AU - Simpson, D.
PY - 2011
SP - 251
EP - 256
DO - 10.5220/0003164902510256
PB - SciTePress