Clustering of Data that Quantify the Degree of Impairment of the Upper Limb in Patients with Alterations of the Central Nervous System

Leonardo Anaya, Ivett Quinones, Yannick Quijano, Virginia Bueyes, Enrique Chong, Victor Ponce

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Resumen

Previous studies have considered improving the classification procedures for motor impairment of the upper limb in patients with Central Nervous System alterations. This work compares two classification methods to be able to group the SSULF scale into five classes to have a better assessment, results showed that with the K-Means more than the 95% of the control group SALM values were correctly classified in SSULF 1 and with the Fuzzy C-means the 92%, so we can assume that the K-means method did a better classification for our purpose.

Idioma originalInglés
Título de la publicación alojada2020 17th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2020
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728189871
DOI
EstadoPublicada - 11 nov. 2020
Evento17th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2020 - Virtual, Mexico City, México
Duración: 11 nov. 202013 nov. 2020

Serie de la publicación

Nombre2020 17th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2020

Conferencia

Conferencia17th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2020
País/TerritorioMéxico
CiudadVirtual, Mexico City
Período11/11/2013/11/20

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