Eye-Tracking technology is a tool for collecting data on a person’s visual attention and is suitable for psychological and physiological studies (e.g. reading and psychological response studies). The data captured can provide us a number of statistics regarding the participant’s interaction with stimuli. With selected areas of interest within visual stimuli provided to the participant, we can take numerous measurements (e.g. the time taken to first fixation, the total number of fixations, the total duration of all fixations etc.) The technology has already been used within healthcare-related research with positive outcomes in distinguishing patterns and metrics among different groups of users. Our hypothesis is that this data can be used to infer the competency of interpreters of clinical bedside monitors. A PhD study has been designed to capture the eye gaze and scan-path of nurses with mixed levels of expertise (nursing undergraduates to practicing nurses) whilst they interpret a simulated bedside monitor. During this recording, they will verbalise their interpretation and they will be given a score according to set criteria (validated by nursing experts at Ulster University). We expect this data when analysed will show quantitative differences that distinguish users as experts, competent and lacking competency. The captured data can be transformed into metrics for determining proficiency whilst reading and interpreting vital signs on a bedside monitor. These could be used within patient monitoring training as another form of assessment during a simulation.
|Title of host publication||Unknown Host Publication|
|Publisher||Irish Human Computer Interaction Conference|
|Number of pages||1|
|Publication status||Published - 23 Oct 2015|
|Event||Irish Human Computer Interaction - Dublin|
Duration: 23 Oct 2015 → …
|Conference||Irish Human Computer Interaction|
|Period||23/10/15 → …|
- Health Informatics
- Eye tracking
Currie, J., Bond, R., McCullagh, P., Black, P., & Finlay, D. (2015). Using Eye-Tracking Technology to Capture Visual Attention during Interpretation of a Simulated Bedside Monitor. In Unknown Host Publication Irish Human Computer Interaction Conference.