Comparison of extreme learning machine and neural network method on hand typist robot for quadriplegic person

Abstract

On this paper, the predicted results of the two types of methods will compare. This is very important because, the error in the determination method will cause the prediction result is not optimal. Two types of methods to be coordinated are the Extreme Learning Machine and Back propagation Neural Network. Testing will be done by entering the calculation from each method to Hand Typist Robot to perform the same task. This robot is used to help Quadriplegic Person in operating a computer keyboard and has 4 Degrees of Freedom (DOF) in both arms. The actuator for all DOFs is Dynamixel AX-12A. This robot processed CMPS10 sensor data which sense the changes provided by Quadriplegic Person. The change of motion will be processed using a method to predict the movement of each Dynamixel AX-12A motor. The most optimal method will produce the lowest Mean Square Error (MSE).