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Joint trajectory generator for powered orthosis based on gait modelling using PCA and FFT

Published online by Cambridge University Press:  06 November 2017

Nicholas B. Melo*
Affiliation:
Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil. E-mails: [email protected], [email protected], [email protected]
Carlos E. T. Dórea
Affiliation:
Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil. E-mails: [email protected], [email protected], [email protected]
Pablo J. Alsina
Affiliation:
Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil. E-mails: [email protected], [email protected], [email protected]
Márcio V. Araújo
Affiliation:
Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil. E-mails: [email protected], [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]

Summary

In this work, we propose a method able to find user-oriented gait trajectories that can be used in powered lower limb orthosis applications. Most research related to active orthotic devices focuses on solving hardware issues. However, the problem of generating a set of joint trajectories that are user-oriented still persists. The proposed method uses principal component analysis to extract shared features from a gait dataset, taking into consideration gait-related variables such as joint angle information and the user's anthropometric features, used directly in an orthosis application. The trajectories of joint angles used by the model are represented by a given number of harmonics according to their respective Fourier series analyses. This representation allows better performance of the model, whose capability to generate gait information is validated through experiments using a real active orthotic device, analysing both joint motor energy consumption and user metabolic effort.

Type
Articles
Copyright
Copyright © Cambridge University Press 2017 

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