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Title:: Obtainment of Sub Thalamic Nucleus Neuron Key Parameters and Variables base on Unscented Kalman Filter

Author(s):: WANG Haiyang; WANG Jiang; CHEN Yingyuan; 1.School of Mechanical Engineering, Baicheng Normal College, Baicheng Jilin 137000, China；2.School of Electrical and Automation Eng., Tianjin University, Tianjin 300072, China

Keywords:: Deep brain stimulation(DBS); Unscented Kalman filter（UKF）; Key parameter; Parkinson; Adaptive synchronization; State variables; Ion channels .

摘要:: 为了获取脑部神经一些不可测量的关键参数和变量。本研究提出以可测量的神经元膜电位为基础，通过无迹卡尔曼滤波(Unscented kalman filter, UKF)实时估计，实现关键参数和关键变量的获取。本研究以Sub Thalamic Nucleus (STN) 神经元为研究对象，应用以上的方法分别实现了单个参数（钠离子通道电导gNa）的估计、多个参数（钠离子通道电导gNa，钾离子通道电导gk）的同时估计，以及多个变量（r、n、h及Ca离子浓度）的同时估计，证明了该方法的可行性。本研究还给出了UKF方法和自适应同步方法的对比，进一步证明了UKF方法的有效性。本研究提出的方法可以正确的估计出所需的关键参数和变量，对神经活动的外部电磁控制成为可能，对临床神经疾病的诊断和治疗具有重要的意义。

Abstract:: In order to get some key parameters and key variables, a scheme was brought forward in this paper, which was using UFK（unscented kalman filter）to estimate these key parameters and variables along with neurons membrane potential changing in real time. Taking Sub Thalamic Nucleus (STN) neurons as research objects, this paper accomplish single parameter estimation and multiple parameter estimation and estimates of multiple variables were accomplished. All the results showed that using UKF to estimate these key parameters and variables was feasible. The methods in this paper are important significance in neurologic diseases, which can controlling neural activity possiblely by applying external electromagnetic field.