Biomedical Diagnosis of Infant Cry Signal Based on Analysis of Cepstrum by Deep Feedforward Artificial Neural Networks

Abstract

The automatic analysis and detection of audio signals is an important field of research with promising applications in various biomedical engineering problems such as speech, heart murmur, and lung sound analysis and classification. In this regard, automatic classification of infant vocalizations is becoming an appealing research area for medical diagnosis in clinical milieu. Indeed, the analysis and classification of infant cry records is a conventional non-inva-sive technique to distinguish between healthy and unhealthy infants.