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dc.contributor.authorHernández Martínez, Henry
dc.contributor.authorMontiel Ariza, Holman
dc.contributor.authorGaviria Roa, Luz Andrea (1)
dc.description.abstractSome case studies treated by physiotherapists or orthopedists to measure the alignment of the lower extremities during a gait cycle are based on empirical methods of visual observation. This methodology does not guarantee total success, since it depends on the experience of the specialist, what can cause irreversible damage to patients, such as: hip displacement, wear and overload of the joints of a single lower limb. Although, this problem has been addressed in the investigation by means of devices implementation with sensors or methods of processing sequences of images and videos, this topic is still under investigation because the current methods depend on many external elements and data given by an expert in the area. Therefore, this paper proposes a partial solution to this problem by systematizing the experience of a specialist through a computational learning method.es_ES
dc.publisherTelkomnika (Telecommunication Computing Electronics and Control)es_ES
dc.relation.ispartofseries;vol. 18, nº 4
dc.subjectartificial neural networkes_ES
dc.subjectcomputational learning methodes_ES
dc.subjectdeep learninges_ES
dc.titleStrategy to determine the foot plantar center of pressure of a person through deep learning neural networkses_ES
dc.typeArticulo Revista Indexadaes_ES

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