Infant Cry Detection and Pain Scale Assessment: A Pilot Study

Infant Cry Detection and Pain Scale Assessment: A Pilot Study

N. Sriraam, S. Tejaswini
Copyright: © 2014 |Pages: 10
DOI: 10.4018/ijbce.2014010104
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Abstract

A biological alarm system that connects mother and new born is referred as infant cry. Infant cry is a first means of communication through which mother understands the level of distress/ needs. Infant cry can be considered a multimodal behavior which involves limb movements, facial expressions which changes over time to identify the needs of an infant. The cry of the baby cannot be predicted accurately and it is hard to identify for what it cries for. The infant's cry is mainly a vocal signal which is a way of communication that aims to get attention of the listener to a physical state like hunger, pain, discomfort, fear, illness, wet diaper etc., .Pain is one of the most common symptoms experienced world over. Pain is an unpleasant feeling that is conveyed to the brain by sensory neurons. The discomfort signals actual or potential injury to the body. This pilot study gives an insight on the current state of works in infant cry analysis and pain scale assessment and also concludes with thoughts about the future directions for better representation and interpretation of infant cry signals.
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2.1. Infant Cry

The infant cry signal used for the study is taken from Chillanto, Mexican data base which is used for the study of characteristics of the cry with conditions such as normal, pain, hunger, deaf and Asphyxia. The full recording and the segmented of each recording are used as the preliminary study infant cry recordings. The data base gives us the details about all the mentioned cry and these cries can be used reference for the recorded cry in this project. It is similar to Automatic Speech Recognition system process which comprises two main stages. They are signal processing and pattern classification. The main aim of this system is to discriminate the different types of cries and identify the pathology cry. In signal processing step raw cry signal is preprocessed such as cleaning, filtering and normalization. Then smoothed signal is analyzed and by suitable feature extraction techniques the salient features are derived.

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