Optimized Artificial Neural Network for Biosignals Classification Using Genetic Algorithm

The artificial neural networks (ANNs) are increasingly being used to solve the problem of pattern recognition, but it is an arduous task for their designer to obtain the optimal topology to be used for ANN training since this is considered a very difficult problem. Even after several tests, the optimized topology may not be reached. A possible solution for this problem is the use of a hybrid intelligent system; an optimization technique is used together with the ANN in order to search for an optimized topology. This paper applies this concept, using the genetic algorithms for the optimization of the topology of a multilayer perceptron, used for the classification of wrist orientation, muscle contraction levels and subjective parameters of the voice. The data were preprocessed with wavelet packet transform. The tool presents promising results above 96% all the way up to 99% of total hits, with 98% and 90% reliability.