Estimation of hidden state variables of the intracranial system using constrained nonlinear Kalman filters.
Estimation of hidden state variables of the intracranial system using constrained nonlinear Kalman filters.
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使用约束非线性卡尔曼滤波器估计颅内系统的隐藏状态变量。
DOI:
10.1109/iembs.2005.1615763
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发表时间:
2005
期刊:
影响因子:
--
通讯作者:
Bergsneider,Marvin
中科院分区:
文献类型:
--
作者:
Hu,Xiao;Nenov,Valeriy;Vespa,Paul;Bergsneider,Marvin
Impeded by the rigid skull, assessment of physiological variables of the intracranial system is difficult. A hidden state estimation approach is used in the present work to facilitate the estimation of unobserved variables from available clinical measurements including intracranial pressure (ICP) and cerebral blood flow velocity (CBFV). The estimation algorithm is based on a modified nonlinear intracranial mathematical model, whose parameters are first identified in an offline stage using a nonlinear optimization paradigm. Following the offline stage, an online filtering process is performed using a nonlinear Kalman filter (KF)-like state estimator that is equipped with a new way of deriving the Kalman gain satisfying the physiological constraints on the state variables. The proposed method is then validated by comparing different state estimation methods and input/output (I/O) configurations using simulated data. It is also applied to a set of CBFV, ICP and arterial blood pressure (ABP) signal segments from brain injury patients. The results indicated that the proposed constrained nonlinear KF achieved the best performance among the evaluated state estimators and that the state estimator combined with the I/O configuration that has ICP as the measured output can potentially be used to estimate CBFV continuously. Finally, the state estimator combined with the I/O configuration that has both ICP and CBFV as outputs can potentially estimate the lumped cerebral arterial radii, which are not measurable in a typical clinical environment.
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作者:
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DOI:
--
发表时间:
1985
期刊:
Journal of immunology (Baltimore, Md. : 1950)
影响因子:
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--
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影响因子:
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