Feasibility of EEG to monitor cognitive performance during venous cannulation: EEG Distracted Intravenous Access (E-DIVA)

David J Lowe, Scott A James, Adam Lloyd, Gareth R Clegg

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

BACKGROUND: The feasibility study aims to evaluate the use of EEG in measuring workload during a simulated intravenous cannulation task. Cognitive workload is strongly linked to performance, but current methods to assess workload are unreliable. The paper presents the use of EEG to compare the cognitive workload between an expert and novice group completing a simple clinical task.

METHODS: 2 groups of volunteers (10 final year medical students and 10 emergency medicine consultants) were invited to take part in the study. Each participant was asked to perform 3 components of the simulation protocol: intravenous cannulation, a simple arithmetic test and finally these tasks combined. Error rate, speed of task completion and an EEG-based measure of cognitive workload were recorded for each element.

RESULTS: EEG cognitive workload during the combined cannulation and arithmetic task is significantly greater in novice participants when compared with expert operators performing the same task combination. EEG workload mean measured for novice and experts was 0.62 and 0.54, respectively (p=0.001, 95% CI 0.09 to 0.30). There was no significant difference between novice and expert EEG workload when the tasks were performed individually.

CONCLUSIONS: EEG provides the opportunity to monitor and analyse the impact of cognitive load on clinical performance. Despite the significant challenges in set up and protocol design, there is a potential to develop educational interventions to optimise clinician's awareness of cognitive load. In addition, it may enable the use of metrics to monitor the impact of different interventions and select those that optimise clinical performance.

Original languageEnglish
Pages (from-to)68-72
Number of pages5
JournalBMJ Simulation & Technology Enhanced Learning
Volume2
Issue number3
Early online date1 Jun 2016
DOIs
Publication statusE-pub ahead of print - 1 Jun 2016

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