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Markovians systems to estimate absolute angles in lower limb exoskeletons

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Samuel Lourenço Nogueira
Total Authors: 1
Document type: Doctoral Thesis
Press: São Carlos.
Institution: Universidade de São Paulo (USP). Escola de Engenharia de São Carlos
Defense date:
Examining board members:
Adriano Almeida Gonçalves Siqueira; Anselmo Frizera Neto; Eduardo Rocon de Lima; Arlindo Neto Montagnoli; Marco Henrique Terra
Advisor: Adriano Almeida Gonçalves Siqueira

In this thesis are presented global estimation systems based on Markov models applied in robotic rehabilitation area. The proposed systems have been developed to estimate the angular positions of the exoskeletons for lower limbs, designed to provide motor rehabilitation of stroke and spinal cord injured people. Filters based on the Kalman filter, one nominal and other considering uncertainties in the model, were used in sensor data fusion strategies from inertial sensors, to estimate angular positions. Genetic algorithms are used to the optimization of filters, tuning the weighting matrices. In opposition to these modelling via local estimation, using only one inertial unit, we also chose a global modelling getting the best information from each sensor, combining them in a Markov model. Experimental results with an exoskeleton were used to compare the Markovian approach to conventional. (AU)

FAPESP's process: 12/05552-9 - Robust system for estimation of absolute angular positions and force interaction for exoskeletons of lower limbs
Grantee:Samuel Lourenço Nogueira
Support type: Scholarships in Brazil - Doctorate