EMG monitoring system using fast fourier transform and a fuzzy logic classifier.
Salazar Camacho, Esteban José
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This thesis presents the design of an EMG (Electrornyographic) signal monitoring system that senses the human hand. This system classifíes the hand fingers motion and sends an output signal that can be used for a motion controller. The myoelectric signals aríse from the contraction or relaxaron of a muscle. The EMG signals can be used as an input for a control system using a communication interface supported with electronic devices in order to perform the human machine interaction. The sensors and the myoelectric signal acquisition used in this work are commercially availabie superficial electrodes, while the fuzzy logic algorithms and signal processing systems are developed in this thesis. The acquisition system designed is able to amplify the input EMG and then a filter ptocedure eliminates the parasite and instrumentation noises, allowing the monitoring system to interpret the signaí pattern and respond to the user motion.