m+Medelevator.RU
← Поиск публикаций
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2014

An automatized system for the assessment of nutritive sucking behavior in infants: a preliminary analysis on term neonates.

СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Tamilia E, Delafield J, Fiore S, Taffoni F

Аннотация

Nutritive Sucking (NS) is a highly organized process that can reflect infants' maturation during the early post-natal period. The assessment of NS may provide a sensitive means of evaluating early motor skills and their development. Thus, a reliable tool for assessing sucking behavior may benefit diagnostics and treatment of newborns since the first days of life. The aim of this work is to propose an automatized system to measure sucking ability and calculate a set of objective and quantitative indices for its assessment. We focused on the analysis of the Intraoral Pressure (IP) generated by infants while feeding: an ad-hoc designed software application was developed to analyze the signal obtained by a pressure transducer connected with a catheter placed through a standard bottle teat into the oral cavity during feeding. Automatic algorithms for suck and burst identification and for their characterization are described. We carried out a preliminary test of the system, analyzing data from two healthy term newborns, tested twice over time (1-2 days old and 6-10 weeks later). We calculated a set of different sucking parameters (e.g. sucking amplitude, frequency and area), and proposed some indices, that are typically used for the assessment of motor control, in order to assess the smoothness of IP. Results encourage further investigation of the proposed system for monitoring the development of early sucking skills.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты