Abstract
Technologies for automated detection of neonatal seizures are gradually moving towards cot-side implementation. The aim of this paper is to present different ways to visualize the output of a neonatal seizure detection system and analyse their influence on performance in a clinical environment. Three different ways to visualize the detector output are considered: a binary output, a probabilistic trace, and a spatio-temporal colormap of seizure observability. As an alternative to visual aids, audified neonatal EEG is also considered. Additionally, a survey on the usefulness and accuracy of the presented methods has been performed among clinical personnel. The main advantages and disadvantages of the presented methods are discussed. The connection between information visualization and different methods to compute conventional metrics is established. The results of the visualization methods along with the system validation results indicate that the developed neonatal seizure detector with its current level of performance would unambiguously be of benefit to clinicians as a decision support system. The results of the survey suggest that a suitable way to visualize the output of neonatal seizure detection systems in a clinical environment is a combination of a binary output and a probabilistic trace. The main healthcare benefits of the tool are outlined. The decision support system with the chosen visualization interface is currently undergoing pre-market European multi-centre clinical investigation to support its regulatory approval and clinical adoption.
Highlights
Neonatal seizures are the most common neurological emergency in the neonate and are a serious concern for clinicians and parents worldwide [1]
Despite the fact that many short and focal neonatal seizures are undetectable with aEEG and interobserver agreement is poor [5], aEEG currently serves as a trade-off between very inaccurate clinical detection of seizures and
The results of visualization methods along with the system validation results indicate that the developed neonatal seizure detector with its current level of performance would unambiguously be of benefit to clinicians as a decision support system (DSS) and will increase the neonatal seizure detection rate
Summary
Neonatal seizures are the most common neurological emergency in the neonate and are a serious concern for clinicians and parents worldwide [1]. Interpretation of neonatal EEG requires a neurophysiologist or paediatric neurologist with specific expertise in neonatal EEG. This expertise is not available on a 24 h basis, 7 days a week [3]. To fill the gap in the lack of availability of experts, clinical staff in the NICU are using a simpler form of EEG monitoring, called amplitude integrated EEG or aEEG [4]. Despite the fact that many short and focal neonatal seizures are undetectable with aEEG and interobserver agreement is poor [5], aEEG currently serves as a trade-off between very inaccurate clinical detection of seizures and very accurate but scarcely available neurophysiologic expertise, and is widely adopted worldwide in the NICU [3]
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