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2023 | OriginalPaper | Chapter

Infant Crying Patterns’ Analysis Using Machine Learning

Authors : Viktoria-Nikoleta Tsakalidou, Eleni Vrochidou, George A. Papakostas

Published in: Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems

Publisher: Springer Nature Singapore

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Abstract

Communication is the most important process for a living organism. Autism is a complex developmental disorder that causes communication problems. The only way to communicate for babies is through crying, so screening analysis is an attractive approach to early diagnosis of autism to improve recovery. The aim of this paper is to explore the potential of machine learning (ML) in babies’ crying decoding toward autism diagnosis, pain identification, baby needs, etc. An extended literature review on the subject has been made to provide sensible comparisons between recently introduced ML approaches. Research findings reveal that ML can facilitate infant needs decoding and early diagnosis through crying pattern analysis; however, available infant crying datasets are scarce.

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Title: Infant Crying Patterns’ Analysis Using Machine Learning
Authors: Viktoria-Nikoleta Tsakalidou
Eleni Vrochidou
George A. Papakostas
Publisher: Springer Nature Singapore
Book: Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems
Print ISBN: 978-981-19-7752-7

Electronic ISBN: 978-981-19-7753-4

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-981-19-7753-4_51

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