Characteristics of lung sounds in early infants using automated analysis.
Journal:
European journal of pediatrics
PMID:
40358760
Abstract
UNLABELLED: A new lung sound analysis software program has been developed. It can automatically select a typical lung sound spectrogram and calculate lung sound parameters using machine learning programs. This study aimed to clarify lung sound characteristics in early infants using this program. Using the program, the characteristics of lung sounds in healthy 1- and 4-month-old infants were examined. The lung sounds were assessed in the supine position for 1-month-old infants and in both the sitting and supine positions for 4-month-old infants. We compared the characteristics of the infant lung sounds with those of healthy 3-year-old children. The lung sound parameters of the 1-month-old infants (n = 58) were affected by gender, height, and birth weight. However, those of the 4-month-old infants (n = 50) obtained in the sitting or supine position were not affected by these factors in the study. The lung sound parameters obtained in the sitting and supine positions were not significantly different, and they were not related to a history of wheezing or allergy. PAP was higher for the 1-month-old infants than for the 4-month-old infants, and RPF and RPF were also higher for the 1-month-old infants than for the 4-month-old infants. The PAP, FAP, RPF, RPF, A, and B of the 4-month-old infants were significantly higher than those of the 3-year-old children (n = 80).