Response classication in psychological testing using a neural network

A feedforward neural network with error backpropagation has been designed to recognize hand-drawn patterns in a cognitive test. The architecture uses both position and direction sensitivity in the input layer. The training set consisted of 659 icons which were shifted horizontally and vertically to give a total training set of 5931 icons. In testing on an independent set of 31,192 icons produced by 557 subjects from a Danish standard population sample, the rate of misclassification was 0.12% compared with an average rate of sequence errors of 1.6%.