| Título |
Clustering of Data that Quantify the Degree of Impairment of the Upper Limb in Patients with Alterations of the Central Nervous System |
| Tipo |
Congreso |
| Sub-tipo |
Memoria |
| Descripción |
2020 17th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2020 |
| 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. © 2020 IEEE. |
| Observaciones |
DOI 10.1109/CCE50788.2020.9299168 |
| Lugar |
Ciudad de México |
| País |
Mexico |
| No. de páginas |
Article number 9299168 |
| Vol. / Cap. |
|
| Inicio |
2020-11-11 |
| Fin |
2020-11-13 |
| ISBN/ISSN |
9781728189871 |
