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Pathological Tremor and Voluntary Motion Modeling and Online Estimation for Active Compensation

Antonio Bo 1 Philippe Poignet 2, 1 Christian Geny 3
1 DEMAR - Artificial movement and gait restoration
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
2 DEXTER - Conception et commande de robots pour la manipulation
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : This paper presents an algorithm to perform online tremor characterization from motion sensors measurements, while filtering the voluntary motion performed by the patient. In order to estimate simultaneously both nonstationary signals in a stochastic filtering framework, pathological tremor was repre- sented by a time-varying harmonic model and voluntary motion was modeled as an auto-regressive moving-average (ARMA) model. Since it is a nonlinear problem, an extended Kalman filter (EKF) was used. The developed solution was evaluated with sim- ulated signals and experimental data from patients with different pathologies. Also, the results were comprehensively compared with alternative techniques proposed in the literature, evidencing the better performance of the proposed method. The algorithm presented in this paper may be an important tool in the design of active tremor compensation systems.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00522952
Contributor : Philippe Poignet <>
Submitted on : Monday, October 4, 2010 - 8:56:52 AM
Last modification on : Tuesday, March 9, 2021 - 5:09:20 PM

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  • HAL Id : lirmm-00522952, version 1

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Antonio Bo, Philippe Poignet, Christian Geny. Pathological Tremor and Voluntary Motion Modeling and Online Estimation for Active Compensation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, Institute of Electrical and Electronics Engineers, 2011, 19 (2), pp.177-185. ⟨lirmm-00522952⟩

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