448.3 - The use of Hololens increases the engagement while reducing the cognitive load of senior medical students when overlaying medical imaging of body donors during the dissection
Presenting Author University of California, San Diego, McGill University
Augmented reality (AR) has recently been implemented in medicine as an integrative way to view virtual objects while simultaneously interacting with the physical environment. The technology offers many benefits for education in fields that require interactive and visual learning activities, such as human anatomy. However, AR is a novel and very advanced technology, so justifying its use in the field or classroom necessitates extensive study of its effects on mental processes. Accordingly, the purpose of this study was to evaluate cognitive markers of students’ engagement and cognitive load while they used AR technology to overlay donor-specific diagnostic imaging (DSDI) onto the corresponding body donors in a fourth-year medical elective course at McGill University. Each participnt (n = 12) used DSDI on a head-mounted Microsoft HoloLens and DSDI on an Apple iPad to examine the underlying anatomy of their assigned body donor before beginning their dissection. Participants wore portable five-lead electroencephalographic (EEG) devices to collect cognitive processing data. Engagement (engagement index; EI) and cognitive load (theta-alpha ratio; TAR) were compared between HoloLens and iPad use conditions. Mean EI under the HoloLens condition (0.499 ± 0.038) was significantly higher than the mean EI under the iPad condition (0.297 ± 0.037; P = 0.002) while the mean TAR under the HoloLens condition (1.508 ± 0.047) was significantly lower than that collected during the iPad trial (1.813 ± 0.071; P = 0.012). Together, these results indicate that use of the HoloLens to superimpose radiographic images onto a human cadaver during dissection is significantly more engaging than examining the same images on a 2D iPad screen, and also imposes a lesser cognitive load for the same task.
Figure 1. Mean engagement index (EI) values calculated from electroencephalographic data collected under the baseline, iPad, and HoloLens conditions (n = 12). All EI values are expressed as unitless ratios (beta wave amplitude divided by the sum of theta and alpha wave amplitudes) representing engagement. Error bars represent the standard error of the mean; significant differences (*) were declared at P ≤ 0.05; Figure 2. Mean theta-alpha ratio (TAR) values calculated from electroencephalographic data collected under the baseline, iPad, and HoloLens conditions (n = 12). All TAR values are expressed as unitless ratios (theta wave amplitude divided by alpha wave amplitude) representing cognitive load. Error bars represent the standard error of the mean; significant differences (*) were declared at P ≤ 0.05.
