Asphyxiated infant cry classification using Simulink model

Infant Cry is the only communication for infant to express their feeling. It has been proven by numerous reports that infant cry can be used to detect asphyxia using appropriate signal processing technique. This paper presents the classification of infant cries with asphyxia using a Simulink model developed for a digital signal processor. The main components of the model are Mel Frequency Cepstrum Coefficients and Multilayer Perceptron Neural Network. The cry signal feature was extracted using Mel Frequency Cepstrum Coefficients analysis and the asphyxiated cry was classified using Multilayer Perceptron Neural Network. The Simulink model is able to discriminate between asphyxiated and normal infant cry signals.