Infection prevention and early warning in neonatal intensive care unit based on physiological sensor monitoring

Abstract

The infection rate in the Neonatal Intensive Care Unit (NICU) is very high, which is also one of the important causes of morbidity and even death in critically ill neonates and premature infants. At present, the monitoring system of the Neonatal Intensive Care Unit is not very complete, and it is difficult to provide early warning of neonatal illness. Coupled with the untimely response measures, it has brought certain difficulties to the ward’s infection prevention and control work. The rapid development of the Internet of Things (IoT) in recent years has made the application fields of various sensor devices more and more extensive. This paper studied infection prevention and early warning in the Neonatal Intensive Care Unit based on physiological sensors. Combined with a wireless network and physiological sensors, this paper built an intelligent monitoring system for the Neonatal Intensive Care Unit, which aimed to monitor various physiological data of newborns in real-time and dynamically, and gave early warning signals, so that medical staff could take preventive measures in time. The experiments showed that the monitoring system proposed in this paper could obtain the physiological information of neonates in time, which brought convenience to prevention and early warning work, and reduced the infection rate of neonatal wards by 7.39%.