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首页> 外文期刊>Journal of Biomedical Science and Engineering >Efficient hemodynamic states stimulation using fNIRS data with the extended Kalman filter and bifurcation analysis of balloon model
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Efficient hemodynamic states stimulation using fNIRS data with the extended Kalman filter and bifurcation analysis of balloon model

机译：使用fNIRS数据和扩展的Kalman滤波器以及球囊模型的分叉分析来进行有效的血液动力学状态刺激

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This paper introduces a stochastic hemodynamic system to describe the brain neural activity based on the balloon model. A continuous-discrete extended Kalman filter is used to estimate the nonlinear model states. The stability, controllability and observability of the proposed model are described based on the simulation and measurement data analysis. The observability and controllability characteristics are in- troduced as significant factors to validate the preference of different hemodynamic factors to be considered for diagnosis and monitoring in clinical applications. This model also can be efficiently applied in any monitoring and control platform include brain and for study of hemodynamics in brain imaging modalities such as pulse oximetry and functional near infrared spectroscopy. The work is on progress to extend the proposed model to cover more hemodynamic and neural brain signals for real-time in-vivo application.
机译：本文介绍了一种基于球囊模型的随机血液动力学系统，用于描述脑神经活动。连续离散扩展卡尔曼滤波器用于估计非线性模型状态。基于仿真和测量数据分析，描述了所提模型的稳定性，可控制性和可观察性。引入可观察性和可控性特征作为重要因素，以验证临床应用中诊断和监测要考虑的不同血液动力学因素的偏好。该模型还可以有效地应用于包括大脑在内的任何监视和控制平台，并用于研究脑成像模式（例如脉搏血氧饱和度法和功能性近红外光谱法）中的血液动力学。正在进行的工作正在扩展所提出的模型，以涵盖更多的血液动力学和神经脑信号以进行实时体内应用。

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