期刊
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
卷 69, 期 7, 页码 2370-2378出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2022.3144094
关键词
Pediatrics; Pressure measurement; IP networks; Hospitals; Artificial neural networks; Pressure sensors; Feature extraction; Infant; Non nutritive sucking; prediction; sensitized pacifier
Due to the lack of physical development, premature infants require assistance in improving their sucking skills. Here, we present a new device that can measure intraoral pressure and expression pressure as parameters for non-nutritive sucking skills. This device provides a robust and inexpensive alternative for monitoring oral feeding ability in premature infants.
Due to the lack of enough physical or suck central pattern generator (SCPG) development, premature infants require assistance in improving their sucking skills as one of the first coordinated muscular activities in infants. Hence, we need to quantitatively measure their sucking abilities for future studies on their sucking interventions. Here, we present a new device that can measure both intraoral pressure (IP) and expression pressure (EP) as ororhithmic behavior parameters of non-nutritive sucking skills in infants. Our device is low-cost, easy-to-use, and accurate, which makes it appropriate for extensive studies. To showcase one of the applications of our device, we collected weekly data from 137 premature infants from 29 week-old to 36 week-old. Around half of the infants in our study needed intensive care even after they were 36 week-old. We call them full attainment of oral feeding (FAOF) infants. We then used the Non-nutritive sucking (NNS) features of EP and IP signals of infants recorded by our device to predict FAOF infants' sucking conditions. We found that our pipeline can predict FAOF infants several weeks before discharge from the hospital. Thus, this application of our device presents a robust and inexpensive alternative to monitor oral feeding ability in premature infants.
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