Classification of chronic whiplash associated disorders with artificial neural networks

This study present a new method for classification of subjects suffering from whiplash associated disorders (WAD) with a supervised resilient backpropagation neural network (BPN). The only input needed, from each subject, is features extracted from 3-dimensional motion data collected by a ProReflex system. The analysis with BPN results in a correct prediction for 84% of normal subjects and 89% percent of subjects with WAD.