Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
MICAI '08 Proceedings of the 2008 Seventh Mexican International Conference on Artificial Intelligence
Expert Systems with Applications: An International Journal
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A comparative study of wavelet families for classification of wrist motions
Computers and Electrical Engineering
Objective evaluation of speech dysfluencies using wavelet packet transform with sample entropy
Digital Signal Processing
Modelling and Simulation in Engineering
A new hybrid intelligent system for accurate detection of Parkinson's disease
Computer Methods and Programs in Biomedicine
Hi-index | 12.05 |
A new approach has been presented based on the wavelet packet transform and probabilistic neural network (PNN) for the analysis of infant cry signals. Feature extraction and development of classification algorithms play important role in the area of automatic analysis of infant cry signals. Infant cry signals are decomposed into five levels using wavelet packet transform. Energy and entropy measures are extracted at every level of decomposition and they are used as features to quantify the infant cry signals. A PNN is developed to classify the infant cry signals into normal and pathological and trained with different spread factor or smoothing parameter to obtain better classification accuracy. The experimental results demonstrate that the proposed features and classification algorithms give very promising classification accuracy of 99% and it proves that the proposed method can be used to help medical professionals for diagnosing pathological status of an infant from cry signals.