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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2018 Vol.8(5): 428-436 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2018.8.5.724

Generative Adversarial Networks for Generation and Classification of Physical Rehabilitation Movement Episodes

Longze Li and Aleksandar Vakanski
Abstract—This article proposes a method for mathematical modeling of human movements related to patient exercise episodes performed during physical therapy sessions by using artificial neural networks. The generative adversarial network structure is adopted, whereby a discriminative and a generative model are trained concurrently in an adversarial manner. Different network architectures are examined, with the discriminative and generative models structured as deep subnetworks of hidden layers comprised of convolutional or recurrent computational units. The models are validated on a data set of human movements recorded with an optical motion tracker. The results demonstrate an ability of the networks for classification of new instances of motions, and for generation of motion examples that resemble the recorded motion sequences.

Index Terms—Generative adversarial networks, physical rehabilitation, artificial neural networks.

L. Li is with the Department of Computer Science, University of Idaho, Idaho Falls, ID 83402, USA (longzel@uidaho.edu).
A. Vakanski is with the Industrial Technology, University of Idaho, Idaho Falls, ID 83402, USA (e-mail: vakanski@uidaho.edu).

[PDF]

Cite: Longze Li and Aleksandar Vakanski, "Generative Adversarial Networks for Generation and Classification of Physical Rehabilitation Movement Episodes," International Journal of Machine Learning and Computing vol. 8, no. 5, pp. 428-436, 2018.

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E-mail: ijmlc@ejournal.net