Online pathological tremor characterization using extended Kalman filtering

被引：16

作者：

Bo, Antonio P. L. ^{[1
]}

Poignet, Philippe ^{[1
]}

Widjaja, Ferdinan ^{[2
]}

Ang, Vvei T. ^{[2
]}

机构：

[1] CNRS, UM2, UMR 5506, LIRMM, Montpellier, France

[2] Nanyang Technol Univ, Singapore, Singapore

来源：

2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8 | 2008年

关键词：

D O I：

10.1109/IEMBS.2008.4649516

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper describes different algorithms that perform online pathological tremor characterization in terms of acceleration. Two distinct parametric models are used, an Auto-Regressive (AR) model and an harmonic model. Both models are recursively estimated with Extended Kalman Filters (EKFs). Experimental data was obtained with low cost sensors and the results are compared in terms of spectrogram estimation and prediction performance.

引用

页码：1753 / +

页数：3

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