NEONATAL MONITORING SYSTEM USING ADAPTIVE CLUSTERING ONLINE KALMAN FILTER

  • Vishwa Priya V, 2Dr.R.Renuga Devi

Abstract

Neonatal is health status monitoring continuously and ensue in medical treatments have
resulted in a significant enhance of survival rate in decisively ill infants admitted into Neonatal
Intensive Care Units. The quality of life and long-term health prospects of the neonates depend
increasingly on the reliability and comfort of the monitoring systems. Baby neonatal Incubator is
a closed apparatus used for providing a controlled environment in all the possible ways for the
immense care of premature babies. There are various health parameters such as oxygen level,
temperature, pulse level, respiration pattern which need to be monitored in order to ensure good
health of the neonates. Conventional approaches of baby monitoring in incubators does not
efficiently provide real-time parameter updates and requires constant monitoring of baby
through the presence of nurses or doctors. Hence, modern technologies must be used in order to
track health of infant in the incubator and get updates in any unfavorable condition. In this
proposed analysis and algorithms to produce the best short term and long term prediction. An
adaptive clustering online Kalman filter provides us a very good one-day prediction for each
region. This system is capable of updating the parameters continuously in the system and also
avoids continuous monitoring of the neonates by the person

Published
2020-04-13
How to Cite
Vishwa Priya V, 2Dr.R.Renuga Devi. (2020). NEONATAL MONITORING SYSTEM USING ADAPTIVE CLUSTERING ONLINE KALMAN FILTER. International Journal of Advanced Science and Technology, 29(8s), 2922-2931. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/16176