Automated detection and classification of basic shapes of newborn cry melody

Autism spectrum disorders; Automated analysis and classification; Early diagnosis of neurological impairment; Intensive care management; Newborn infant cry melody; Pre-speech development; Automation; Automated analysis; Early diagnosis; Infant cry; Intensive care; Computer aided diagnosis; Article

Abstract :

[en] The study of newborn cry is a promising non-intrusive and cheap approach to support the early diagnosis of neurodevelopmental disorders. Specifically, cry melody, the trend of the fundamental frequency (f0) over time, could add relevant information to the acoustical analysis of infant crying. To date, the cry analysis is mainly performed by paediatricians/neurologists through a perceptual examination based on listening to the cry and visually inspecting the f0 shape. Therefore, this approach is not widespread as the procedure is operator-dependent and requires a considerable amount of time often prohibitive in daily clinical practice. This paper aims at providing a support to the perceptual analysis through a fully automated method for assessing the melodic shape of newborn cry. Cry units are detected within each recording, even of long duration, and their classification is performed according to five basic melodic shapes (falling, rising, symmetrical, plateau, and complex). The method is tested on synthesized signals and applied to recordings coming from at term healthy newborns. Results are compared to the perceptual analysis performed by trained raters with up to 98% matching. Being contact-less and cheap, this method is well suited for routinely clinical applications and could be effectively related to other clinical parameters for early detection of possible brain injuries or neuro-developmental disorders. © 2018 Elsevier Ltd

Disciplines :

Pediatrics

Author, co-author :

Manfredi, C.; Department of Information Engineering, Università degli Studi di Firenze, Firenze, Italy

Bandini, A.; University Health Network, Toronto Rehabilitation Institute, Toronto, ON, Canada

Melino, D.; Department of Information Engineering, Università degli Studi di Firenze, Firenze, Italy

VIELLEVOYE, Renaud ; Centre Hospitalier Universitaire de Liège - CHU > Département de Pédiatrie > Service néonatologie (CHR)

Kalenga, Masendu ; Université de Liège - ULiège > Département des sciences cliniques > Département des sciences cliniques

Orlandi, S.; Department of Information Engineering, Università degli Studi di Firenze, Firenze, Italy, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada

Language :

English

Title :

Automated detection and classification of basic shapes of newborn cry melody

Publication date :

August 2018

Journal title :

Biomedical Signal Processing and Control

ISSN :

1746-8094

eISSN :

1746-8108

Publisher :

Elsevier Ltd

Volume :

Pages :

174-181

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 03 August 2019

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