Detección de patrones para trabajo en conjunto de EMG y EEG para prótesis de mano

"This work shows proofs of concept for the development of upper limb prostheses control systems, working in conjunction with electromyography (EMG) and electroencephalography (EEG) signals, or also called hybridBCI (hBCI). The work is divided into 3 blocks: EMG/EEG signal collection, signal processing and automatic group classification. 13 users, ages 19 to 23, were invited to the project in order to gather signal samples from 18 distinct hand positions. The classification was performed using K-means as it allows the classification to be automatic and unsupervised. The results obtained verified that it is possible to improve the model when working with both signals together instead of obtaining a model with only EMG signals." -- Tomado del Formato de Documento de Grado.

• Autores: Arciniegas Polanco, José Ricardo
• Fecha de publicación: 2017
• Institución: Universidad de los Andes
• Repositorio: Séneca: repositorio Uniandes
• Idioma: spa
• OAI Identifier: oai:repositorio.uniandes.edu.co:1992/61584
• Acceso en línea: http://hdl.handle.net/1992/61584
• Palabra clave: Aparatos ortopédicos; Electroencefalografía; Electromiografía; Estimulación eléctrica; Ingeniería biomédica; Manos artificiales; Minería de datos; Procesamiento de señales; Sistemas de control
• Rights: openAccess
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/