Browsing by Author "Camues Mosquera, Miguel David"
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Item Clasificación de señales de electroencefalografía para el control de movimientos de los miembros superiores(Universidad Santiago de Cali, 2024) Villamarin Pillimue, Daniel Stiven; Camues Mosquera, Miguel David; Bermeo Varon, Leonardo Anfonio (Director)The loss of upper limbs affects millions of people around the world, creating challenges in their daily lives and limiting their autonomy. New technologies, such as prostheses, are developed every year to improve communication between the user and their environment, contributing to a better quality of life. This study aims to create a system for classifying electroencephalography (EEG) signals of the opening, closing and resting movements of the right- and left-hand using machine learning techniques, seeking to improve the functionality of prostheses for amputees, with greater accuracy. For this purpose, EEG signals were collected using a real-time headset from 15 subjects, 13 typical without amputations and 2 atypical with amputations. Filtering methods, signal processing, time and frequency domain feature extraction were applied. The classifiers used were Random Forest and K-Nearest Neighbors (KNN). The results indicate that Random Forest obtaining the best accuracy, greater than 80%. This study contributes to the advancement in the classification of EEG signals suitable for movement control in the implementation of upper limb prostheses, improving the quality of life of individuals by reducing mental workload and physical effort.