Robot control system using SMR signals detection

Subject Areas : International Journal of Smart Electrical Engineering

faeze asadi ¹ (SYNTECH Technology and Innovation Center)

Received: 2019-05-31 Accepted : 2019-06-21 Published : 2019-03-01

Keywords: Support vector machine, Probabilistic neural network, Feature extraction, Multilayer Perceptron, Brain-computer interface system,

Abstract :

One of the important issues in designing a brain-computer interface system is to select the type of mental activity to be imagined. In some of these systems, mental activity varies with user intent and action that must be controlled by the brain-computer system, and in a number of other signals, the received signals contain the same activity-related mental activity that should be performed by the brain-computer system. Take up The purpose of this paper is to identify and distinguish between multiple movements of the hand, including lifting and lowering the whole hand, from the electromagnetic signal (EEG) signal and the control of a robot by these signals. Since the purpose of using motor signals is selected from the various channels, channels 3c and 4c are selected as the preferred channel. This set of signals in total was about six healthy people. In this paper, support vector machines (SVM), multilayer perceptron (MLP) and probabilistic neural network (PNN) were designed to extract data properties.