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Updated: Jun 24, 2025

Author Spotlight: Implications of Non-Nutritive Sucking on Speech Emergence and Infant Development
Published on: April 19, 2024
Characterization of parameters for the analysis of objective measures of non-nutritive sucking of newborns
Bárbara Generoso Santos de Matos Sales1, Renata Maria Moreira Moraes Furlan2, Camila Alexandra Vilaça Ramos3
1Programa de Pós-graduação em Ciências Fonoaudiológicas, Universidade Federal de Minas Gerais - UFMG - Belo Horizonte (MG), Brasil.
Purpose:
To propose a methodology for analyzing data generated by an instrument measuring non-nutritive sucking pressure in newborns.
Methods:
An analytical observational study was developed, with a cross-sectional design, considering the data collected from 24 full-term newborns without complications. Three collections from each neonate were analyzed, with duration of 2 minutes and a 2-minute interval between them. The defined parameters were extracted using a program developed in Matlab®. The results were obtained by analyzing and comparing 12 variables at a 5% confidence level. Comparison of manual and computerized analyzes was also carried out using the intraclass correlation coefficient.
Results:
The multiple comparison between the three collection moments showed that the significant statistical differences occurred between collections one and two and two and three. When analyzing and comparing each variable separately, it was noted that the second collection showed: greater number of sucking groups, greater number of suctions, less time to start the sucking groups, longer time of sucking groups, less number of sporadic suctions, higher mean pressure values and with less standard deviation, more number of pauses with shorter time of pauses. The intraclass correlation coefficient revealed almost perfect agreement for the 12 evaluated parameters.
Conclusion:
The 12 variables analyzed are relevant, especially in the second collection. The Matlab® program proved to be viable and effective in extracting and analyzing parameters, showing high agreement when compared to manual evaluation.
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