title: Tracking tremor frequency in spike trains using the extended Kalman smoother.
abstract: Tremor is one of the most disabling symptoms in patients with many movement disorders including Parkinson's disease (PD) and essential tremor (ET). Neural tremor manifests itself as a quasi-periodic fluctuation of the firing rate. We describe a frequency tracking method based on the extended Kalman smoother (EKS) to estimate the instantaneous tremor frequency (ITF) exhibited in binary spike trains detected from neural recordings. Simulation results demonstrate that the EKS frequency tracker can estimate the ITF accurately, even though the signal of interest is not sinusoidal and the noise is not Gaussian. The EKS frequency tracker can obtain a normalized mean squared error (NMSE) as low as 0.1 and performs much better than the conventional approach based on the Hilbert transform.
authors.affiliation: Biomedical Signal Processing Laboratory, Department of Electrical & Computer Engineering, Portland State University, OR 97207, USA. sunghan@pdx.edu
authors.forename: Sunghan
authors.initials: S
authors.lastname: Kim
authors.forename: James
authors.initials: J
authors.lastname: McNames
mesh_terms: D000200:Action Potentials; D000465:Algorithms; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D008959:Models, Neurological; D015233:Models, Statistical; D009119:Muscle Contraction; D018482:Muscle, Skeletal / Q000503:physiopathology*; D010363:Pattern Recognition, Automated / Q000379:methods; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes; D013598:Systems Theory; D014202:Tremor / Q000175:diagnosis* / Q000503:physiopathology*