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:
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
影响因子:
--
通讯作者:
Bergsneider,Marvin
Bergsneider,Marvin
中科院分区:
--
文献类型:
--
作者:
Hu,Xiao;Nenov,Valeriy;Vespa,Paul;Bergsneider,Marvin

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由于颅骨坚硬,颅内系统的生理变量的评估是困难的。在目前的工作中使用的隐状态估计方法,以方便估计未观察到的变量,从现有的临床测量,包括颅内压(ICP)和脑血流速度(CBFV)。估计算法是基于一个修改后的非线性颅内数学模型,其参数首先确定在离线阶段使用非线性优化范例。在离线阶段之后,使用非线性卡尔曼滤波器(KF)类状态估计器执行在线滤波过程,该状态估计器配备有导出满足对状态变量的生理约束的卡尔曼增益的新方式。然后,通过比较不同的状态估计方法和输入/输出(I/O)配置,使用模拟数据验证所提出的方法。它也适用于一组脑损伤患者的CBFV,ICP和动脉血压(ABP)信号段。结果表明,所提出的约束非线性卡尔曼滤波器实现了最好的性能之间的评估状态估计器和状态估计器结合的I/O配置,具有ICP作为测量输出可以潜在地用于估计CBFV连续。最后,状态估计器与具有ICP和CBFV两者作为输出的I/O配置相结合,可以潜在地估计在典型临床环境中不可测量的集总脑动脉半径。
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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