Abstract

A new technique is proposed in this paper for real-time monitoring of brain neural activity based on the balloon model. A continuous-discrete extended Kalman filter is used to estimate the nonlinear model states. The stability, controlla- bility and observability of the proposed model are described based on the simulation and measured clinical data analysis. By introducing the controllable and observable states of the hemodynamic signal we have developed a numerical tech- nique to validate and compare the impact of brain signal parameters affecting on BOLD signal variation. This model increases significantly the signal-to-noise-ratio (SNR) and the speed of brain signal processing. A linear-quadratic regulator (LQR) also has been introduced for optimal control of the model.

Highlights

  • In the brain, real-time monitoring of hemodynamic states and preserving their stability provides a significant mechanism for fast and reliable brain monitoring especially in early detection of seizure and epilepsy or in brainmachine interaction studies

  • The stability, controllability and observability of the proposed model are described based on the simulation and measured clinical data analysis

  • By introducing the controllable and observable states of the hemodynamic signal we have developed a numerical technique to validate and compare the impact of brain signal parameters affecting on Blood oxygen level-dependent (BOLD) signal variation

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Summary

Introduction

Real-time monitoring of hemodynamic states and preserving their stability provides a significant mechanism for fast and reliable brain monitoring especially in early detection of seizure and epilepsy or in brainmachine interaction studies. The work presented in [6] uses the Buxton-Fritson model, where the Buxton’s balloon model [7] is added with a damped oscillator to model the blood flow [8] They used a local linearization transfer function in the Kalman filter methodology, allowing physiological noise in addition to the measurement noise. The most popular model to describe the neural activity according to the data from fMRI, is balloon model, which relates BOLD signal to the blood flow. This model is a nonlinear hemodynamic model and the measurements usually have a noisy behavior. These signal components depend on the deoxy-hemoglobin content and render the signal a nonlinear function of v and q

The Extended Balloon Model
The Extended Kalman Filter
E0 1 f ln
Simulation and Measurement Setup
Bifurcation Analysis
Stability
Controllability and Observability
E0 1 f ln 1 E0
The LQR Controller Design
Conclusions

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