[ Diseño de un sistema difuso para el reconocimiento de la actividad muscular en señales de EMG superficiales ]
Volume 19, Issue 4, March 2017, Pages 729–737
Robin Alfonzo Blanco1, Andrés Mauricio Cifuentes Bernal2, and Mauricio Plaza Torres3
1 Posgrados de Ingeniería, Universidad Militar Nueva Granada, Bogotá DC, Colombia
2 Posgrados de Ingeniería, Universidad Militar Nueva Granada, Bogotá DC, Colombia
3 Posgrados de Ingeniería, Universidad Militar Nueva Granada, Bogotá DC, Colombia
Original language: Spanish
Copyright © 2017 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper presents a discussion about the implementation of mechanisms of fuzzy logic for recognizing patterns and parameters in order to predicting the movement intention from a user, through muscle activity in upper and lower members in adult human beings. This information is obtained through reading surface electromyography and is debugged and analyzed by a fuzzy logic system calculated for the prediction of intended movement. A brief comparison between fuzzy sets of straight lines and curved lines is done to determine the best system in generating reliable control orders for prototype robotic exoskeleton type. The fuzzy system designed is Mandani type with nine rules in the inference engine, which had two stages of interaction with samples: one design and other validation, where sought meet an initial threshold of 80 % of effectiveness. Used analog and digital components for data acquisition processes to perform amplification, filtering, digitization and transmission of samples which were implemented in full. The fuzzy system has four input parameters easy obtaining the electromyographic signal input, looking it fast execution at a later real time application. As an important part harmonization by using RMS envelope to make the system more robust against disturbances in the samples. This information is used for generate control commands to an exoskeleton type robotic system to support some user activities.
Author Keywords: EMG, Fuzzy logic, intended movement, forearm, RMS.
Volume 19, Issue 4, March 2017, Pages 729–737
Robin Alfonzo Blanco1, Andrés Mauricio Cifuentes Bernal2, and Mauricio Plaza Torres3
1 Posgrados de Ingeniería, Universidad Militar Nueva Granada, Bogotá DC, Colombia
2 Posgrados de Ingeniería, Universidad Militar Nueva Granada, Bogotá DC, Colombia
3 Posgrados de Ingeniería, Universidad Militar Nueva Granada, Bogotá DC, Colombia
Original language: Spanish
Copyright © 2017 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This paper presents a discussion about the implementation of mechanisms of fuzzy logic for recognizing patterns and parameters in order to predicting the movement intention from a user, through muscle activity in upper and lower members in adult human beings. This information is obtained through reading surface electromyography and is debugged and analyzed by a fuzzy logic system calculated for the prediction of intended movement. A brief comparison between fuzzy sets of straight lines and curved lines is done to determine the best system in generating reliable control orders for prototype robotic exoskeleton type. The fuzzy system designed is Mandani type with nine rules in the inference engine, which had two stages of interaction with samples: one design and other validation, where sought meet an initial threshold of 80 % of effectiveness. Used analog and digital components for data acquisition processes to perform amplification, filtering, digitization and transmission of samples which were implemented in full. The fuzzy system has four input parameters easy obtaining the electromyographic signal input, looking it fast execution at a later real time application. As an important part harmonization by using RMS envelope to make the system more robust against disturbances in the samples. This information is used for generate control commands to an exoskeleton type robotic system to support some user activities.
Author Keywords: EMG, Fuzzy logic, intended movement, forearm, RMS.
How to Cite this Article
Robin Alfonzo Blanco, Andrés Mauricio Cifuentes Bernal, and Mauricio Plaza Torres, “Design of a fuzzy logic system for muscular activity recognition using superficial EMG signals,” International Journal of Innovation and Applied Studies, vol. 19, no. 4, pp. 729–737, March 2017.
