EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model

BioMedical Engineering OnLine

Luciano Luporini Menegaldo¹  Liliam Fernandes de Oliveira³  Kin K Minato² 

[1] Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering, Biomedical Engineering Program (PEB/COPPE), Federal University of Rio de Janeiro, Av. Horácio Macedo 2030, Bloco H-338, 21941-914 Rio de Janeiro, RJ, Brazil

[2] PETROBRAS S/A, Rio de Janeiro, Brazil

[3] School of Physical Education and Sports, Federal University of Rio de Janeiro, Av. Carlos Chagas Filho 540, 21949-900 Rio de Janeiro, RJ, Brazil

关键词: Lower limb muscles;    Muscle force estimation;    EMG-driven models;    Muscle biomechanics;   

Others  :  794998
DOI  :  10.1186/1475-925X-13-37

 received in 2013-12-15, accepted in 2014-03-17,  发布年份 2014

【 摘 要 】

Background

This paper describes the “EMG Driven Force Estimator (EMGD-FE)”, a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results.

Results

An example of the application’s functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown.

Conclusions

The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues.

【 授权许可】

   
2014 Menegaldo et al.; licensee BioMed Central Ltd.

【 图 表 】

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