Cargando…
Using CCA-Fused Cepstral Features in a Deep Learning-Based Cry Diagnostic System for Detecting an Ensemble of Pathologies in Newborns
Crying is one of the means of communication for a newborn. Newborn cry signals convey precious information about the newborn’s health condition and their emotions. In this study, cry signals of healthy and pathologic newborns were analyzed for the purpose of developing an automatic, non-invasive, an...
Autores principales: | Khalilzad, Zahra, Tadj, Chakib |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000938/ https://www.ncbi.nlm.nih.gov/pubmed/36900023 http://dx.doi.org/10.3390/diagnostics13050879 |
Ejemplares similares
-
An Entropy-Based Architecture for Detection of Sepsis in Newborn Cry Diagnostic Systems
por: Khalilzad, Zahra, et al.
Publicado: (2022) -
Newborn Cry-Based Diagnostic System to Distinguish between Sepsis and Respiratory Distress Syndrome Using Combined Acoustic Features
por: Khalilzad, Zahra, et al.
Publicado: (2022) -
Infant Cry Signal Diagnostic System Using Deep Learning and Fused Features
por: Zayed, Yara, et al.
Publicado: (2023) -
Identification of Diseases in Newborns Using Advanced Acoustic Features of Cry Signals
por: Kheddache, Yasmina, et al.
Publicado: (2019) -
Cry-based infant pathology classification using GMMs
por: Farsaie Alaie, Hesam, et al.
Publicado: (2016)