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Master's Dissertation
DOI
https://doi.org/10.11606/D.18.2016.tde-23052016-161930
Document
Author
Full name
Boris Stheven Sullcahuaman Jaúregui
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2016
Supervisor
Committee
Siqueira, Adriano Almeida Gonçalves (President)
Grassi Junior, Valdir
Menegaldo, Luciano Luporini
Title in Portuguese
Método de estimativa de torque da articulação do joelho baseada em EMG
Keywords in Portuguese
EMG
Estimativa de torque
Modelo de contração muscular
Reabilitação
Robótica
Abstract in Portuguese
Este trabalho apresenta um método de estimativa de torque do joelho baseado em sinais eletromiográficos (EMG) durante terapia de reabilitação robótica. Os EMGs, adquiridos de cinco músculos envolvidos no movimento de flexão e extensão do joelho, são processados para encontrar as ativações musculares. Em seguida, mediante um modelo simples de contração muscular, são calculadas as forças e, usando a geometria da articulação, o torque do joelho. As funções de ativação e contração musculares possuem parâmetros limitados que devem ser calibrados para cada usuário, sendo o ajuste feito mediante a minimização do erro entre o torque estimado e o torque medido na articulação usando a dinâmica inversa. São comparados dois métodos iterativos para funções não-lineares como técnicas de otimização restrita para a calibração dos parâmetros: Gradiente Descendente e Quasi-Newton. O processamento de sinais, calibração de parâmetros e cálculo de torque estimado foram desenvolvidos no software MATLAB®; o cálculo de torque medido foi feito no software OpenSim com sua ferramenta de dinâmica inversa.
Title in English
EMG-based method of torque estimation for knee joint
Keywords in English
EMG
Model of muscles contraction
Robotic rehabilitation
Torque estimation
Abstract in English
This work presents a method for knee torque estimation based on electromyographic signals (EMG) during robotic rehabilitation therapy. EMG, taken from five muscles acting during flexion and extension movements of the knee joint, are processed to get the muscle activations. Then, through a simple model of muscle contraction, the forces are computed and knee torque estimated using the joint geometry. Muscle activation and muscle contraction functions have bounded parameters to be adjusted for each user. This adjustment is made by minimizing the error between the estimated torque and the measured torque in the joint computed via inverse dynamics. Two iterative methods for constrained nonlinear optimization are compared, escending Gradient and Quasi-Newton. Signal processing, parameters calibration and estimated torque calculation are developed in the MATLAB® software. Measured torque calculation is performed on OpenSim software using the dynamic inverse tool.
 
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BorisJauregui.pdf (6.18 Mbytes)
Publishing Date
2016-06-02
 
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