The effectiveness of pain management relies on the choice and the correct use of suitable pain assessment tools. In the case of newborns, some of the most common tools are human-based and observational, thus affected by subjectivity and methodological problems. Therefore, in the last years there has been an increasing interest in developing an automatic machine-based pain assessment tool. This research is a preliminary investigation towards the inclusion of a scoring system for the vocal expression of the infant into an automatic tool. To this aim we present a method to compute three correlated indicators which measure three distress-related features of the cry: duration, dysphonantion and fundamental frequency of the first cry. In particular, we propose a new method to measure the dysphonantion of the cry via spectral entropy analysis, resulting in an indicator that identifies three well separated levels of distress in the vocal expression. These levels provide a classification that is highly correlated with the human-based assessment of the cry.

On the automatic audio analysis and classification of cry for infant pain assessment

Elvira Di Nardo;Emilia Parodi;
2019

Abstract

The effectiveness of pain management relies on the choice and the correct use of suitable pain assessment tools. In the case of newborns, some of the most common tools are human-based and observational, thus affected by subjectivity and methodological problems. Therefore, in the last years there has been an increasing interest in developing an automatic machine-based pain assessment tool. This research is a preliminary investigation towards the inclusion of a scoring system for the vocal expression of the infant into an automatic tool. To this aim we present a method to compute three correlated indicators which measure three distress-related features of the cry: duration, dysphonantion and fundamental frequency of the first cry. In particular, we propose a new method to measure the dysphonantion of the cry via spectral entropy analysis, resulting in an indicator that identifies three well separated levels of distress in the vocal expression. These levels provide a classification that is highly correlated with the human-based assessment of the cry.
1
11
https://link.springer.com/epdf/10.1007/s10772-019-09601-0?author_access_token=_hh0Hh7xGiGLnzKh7-mOGPe4RwlQNchNByi7wbcMAY4C0kWqZmD-6QxWtK2E49707w6elKfYNIlv_USBZra9ozNyk-WDSAeDTouSrJMVEE8vE3rW9xx4lwAgyh1Lsw_JFBSleVvtuf1KkHdAHMi5jw==
Infant cry analysis · Machine-based infant pain assessment tool · Spectral entropy analysis
Davide Ricossa, Enrico Baccaglini, Elvira Di Nardo, Emilia Parodi, Riccardo Scopigni
File in questo prodotto:
File Dimensione Formato  
Ricossa2019_Article_OnTheAutomaticAudioAnalysisAnd.pdf

Accesso riservato

Tipo di file: PDF EDITORIALE
Dimensione 3.37 MB
Formato Adobe PDF
3.37 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Paper1.pdf

Accesso aperto

Tipo di file: PREPRINT (PRIMA BOZZA)
Dimensione 1.65 MB
Formato Adobe PDF
1.65 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/1691853
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact