Online Pathological Tremor Characterization Using Extended Kalman Filtering

Antonio Bo 1 Philippe Poignet 2 Ferdinan Widjaja 3 Wei Tech Ang 3
2 DEMAR - Artificial movement and gait restoration
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : This paper describes different algorithms that perform online pathological tremor characterization. Two distinct nonstationary parametric models are used, an Auto-Regressive (AR) model and an harmonic model. The models are recursively estimated with Extended Kalman Filters (EKFs). Experimental data was obtained with low cost accelerometers and the results are compared in terms of spectrogram estimation and prediction performance.
Type de document :
Communication dans un congrès
EMBC: Engineering in Medicine and Biology Conference, Aug 2008, Vancouver, BC, Canada. 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.1753-1756, 2008, 〈10.1109/IEMBS.2008.4649516〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00288836
Contributeur : Philippe Poignet <>
Soumis le : mercredi 18 juin 2008 - 16:47:25
Dernière modification le : jeudi 22 novembre 2018 - 18:12:02

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Antonio Bo, Philippe Poignet, Ferdinan Widjaja, Wei Tech Ang. Online Pathological Tremor Characterization Using Extended Kalman Filtering. EMBC: Engineering in Medicine and Biology Conference, Aug 2008, Vancouver, BC, Canada. 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.1753-1756, 2008, 〈10.1109/IEMBS.2008.4649516〉. 〈lirmm-00288836〉

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