Neonatal intensive care monitoring

Nicklin, Sarah; Wickramasinghe, Y. A. B. D.; Spencer, Stephen Andrew

doi:10.1016/j.cupe.2003.09.006

Cited by 5 publications

(2 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is however difficult to determine at an early stage if the baby's brain is recovering, if brain damage is still a threat or if it already has occurred [1]. At the NICU parameters such as heart rate, blood pressure, oxygen saturation and other measures are monitored regularly [2], but these parameters only assess the general condition of the baby. To monitor the function of the brain itself, a more direct way is to measure the electroencephalogram (EEG): a measure of the Examples of EEG data from the five classes.…”

Section: Introductionmentioning

confidence: 99%

Automatic classification of background EEG activity in healthy and sick neonates

Löfhede

Thordstein

Löfgren³

et al. 2010

J. Neural Eng.

View full text Add to dashboard Cite

The overall aim of our research is to develop methods for a monitoring system to be used at neonatal intensive care units. When monitoring a baby, a range of different types of background activity needs to be considered. In this work, we have developed a scheme for automatic classification of background EEG activity in newborn babies. EEG from six full-term babies who were displaying a burst suppression pattern while suffering from the after-effects of asphyxia during birth was included along with EEG from 20 full-term healthy newborn babies. The signals from the healthy babies were divided into four behavioural states: active awake, quiet awake, active sleep and quiet sleep. By using a number of features extracted from the EEG together with Fisher's linear discriminant classifier we have managed to achieve 100% correct classification when separating burst suppression EEG from all four healthy EEG types and 93% true positive classification when separating quiet sleep from the other types. The other three sleep stages could not be classified. When the pathological burst suppression pattern was detected, the analysis was taken one step further and the signal was segmented into burst and suppression, allowing clinically relevant parameters such as suppression length and burst suppression ratio to be calculated. The segmentation of the burst suppression EEG works well, with a probability of error around 4%.

show abstract

Section: Introductionmentioning

confidence: 99%

Automatic classification of background EEG activity in healthy and sick neonates

Löfhede

Thordstein

Löfgren³

et al. 2010

J. Neural Eng.

View full text Add to dashboard Cite

show abstract

“…It is however difficult to determine at an early stage if the baby's brain is recovering, if brain damage is still a threat or if it already has occurred [1]. At the NICU parameters such as heart rate, blood pressure, oxygen saturation and other measures are monitored regularly [2], but these parameters only assess the general condition of the baby. To monitor the function of the brain itself, a more direct way is to measure the electroencephalogram (EEG); a measure of the electrical signals produced by the brain.…”

Section: Introductionmentioning

confidence: 99%

Soft textile electrodes for EEG monitoring

Löfhede

Seoane

Thordstein

2010

Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine

View full text Add to dashboard Cite

show abstract

A novel approach toward noninvasive monitoring of transcutaneous CO2

Chatterjee

Kostov

et al. 2014

Medical Engineering & Physics

View full text Add to dashboard Cite

The continuous monitoring of transcutaneous gases is an integral part of neonatal intensive care. Present monitors measure the equilibrating values of these gases by raising the skin temperature to 42°C or above. Because neonatal skin is very sensitive and delicate, this often leads to serious skin injuries. In this work, we present a new approach to the noninvasive measurement of transcutaneous partial pressure of carbon dioxide (tcpCO2) based on the initial pseudo steady state diffusion rates instead of the mass-transfer equilibrium. Because we are following initial diffusion rates, each measurement takes no more than a few minutes. Additionally, raising the surface temperature is not required, thus, skin irritation and burns are highly unlikely. A dual-chamber diffusion vessel with either porcine skin or dialysis membrane placed between the two chambers was used to mimic neonatal skin. LI-820 CO2 Analyzer was used to measure the CO2 diffusing through the membrane or skin. Initial experiments on adult human skin under varying physical activities, food intake and breathing patterns showed a strong influence of the various conditions on the amount of CO2 diffusing through skin. These initial findings suggest that this method can be used not only on neonates but to a wider population of patients.

show abstract

Neonatal intensive care monitoring

Cited by 5 publications

References 30 publications

Automatic classification of background EEG activity in healthy and sick neonates

Automatic classification of background EEG activity in healthy and sick neonates

Soft textile electrodes for EEG monitoring

A novel approach toward noninvasive monitoring of transcutaneous CO2

Contact Info

Product

Resources

About