title: Online pathological tremor characterization using extended Kalman filtering.
abstract: This paper describes different algorithms that perform online pathological tremor characterization in terms of acceleration. Two distinct parametricmodels 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.
authors.affiliation: LIRMM UMR 5506 CNRS UM2, Montpellier, France. bo@lirmm.fr
authors.forename: Antônio P L
authors.initials: AP
authors.lastname: Bó
authors.forename: Philippe
authors.initials: P
authors.lastname: Poignet
authors.forename: Ferdinan
authors.initials: F
authors.lastname: Widjaja
authors.forename: Wei T
authors.initials: WT
authors.lastname: Ang
mesh_terms: D000054:Acceleration; D000465:Algorithms; D001698:Biomedical Engineering; D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D008954:Models, Biological; D009068:Movement / Q000502:physiology; D017711:Nonlinear Dynamics; D009862:Online Systems; D012044:Regression Analysis; D014202:Tremor / Q000175:diagnosis* / Q000503:physiopathology*