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Loss of somatosensory feedback in below-the-knee (transtibial) amputees implies a series of changes in the static standing posture, which leads to the affectation of the behavior of the center of pressure (CoP). The performance of two conventional CoP measures used for the characterization of static postural stability (EPE) is validated using unsupervised machine learning algorithms, applied to two population groups: the control group corresponds to non-amputee subjects and the amputee group to subjects with transtibial amputation. Scenarios are required for each of the algorithms using information theory as a classification method, data normalization is performed through binning. In the two CoP measurements (velocity and displacement) two groups were identified, corresponding to the groups examined. A significant difference was observed between the groups, particularly in the CoP velocity, is the best discriminating variable. This study allows professionals interested in the subject to be guided about the variable to be used when analyzing the EPE, as well as making use of the datasets to support the prosthesis alignment part.

Esperanza Camargo Casallas, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

https://orcid.org/0000-0002-3600-4666

Enrique Yamid Garzón, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

https://orcid.org/0000-0001-9498-6349

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Received 2023-03-14
Accepted 2023-09-18
Published 2023-06-26