See-through Visualisation for Training and Assessing Unsighted Physical Examinations

Abstract
Objective: Motivated by the limitations of being unable to provide feedback and adequately assess technical skills whilst training unsighted physical examinations, such as Digital Rectal Examinations (DRE), we present a see-through visualisation system that can be used with benchtop models widely available in medical schools. Methods: We use position and pressure sensors located on the examining finger and have implemented a Virtual Reality (VR) simulation learning tool consisting of registered 3D models of the benchtop, augmented with relevant surrounding pelvic anatomy. The proposed system was evaluated with six medical students and eleven consultants. Results: The system is stable, runs in real time, uses unobtrusive sensor coils and pads, is able to capture data from sensors at 40Hz and adequately translates and rotates the position of the examining finger aligned to the 3D models of the benchtop and surrounding anatomy. Both medical students and consultants recognised the educational value of being able to see-through and visualise surrounding relevant anatomy. Although novices are reported to be the group that could benefit the most from our system, it is crucial not to be over reliant on visual cues for too long and to develop a strategy for the adequate use of the see-through system. Conclusions: The proposed VR simulation system is intended to improve the experience of novices learning unsighted examinations by providing real-time feedback and visualisation, allowing trainees to reflect on their performance and permitting more adequate assessment of technical skills.
Description

        
@inproceedings{
10.2312:vriphys.20171087
, booktitle = {
Workshop on Virtual Reality Interaction and Physical Simulation
}, editor = {
Fabrice Jaillet and Florence Zara
}, title = {{
See-through Visualisation for Training and Assessing Unsighted Physical Examinations
}}, author = {
Granados, Alejandro
and
Perhac, Jan
and
Rosby, Lucy Victoria
and
Lee, Yee Mun
and
Tan, Glenn Wei Leong
and
Tan, Tai Chi
and
Higham, Jenny
and
Thalmann, Nadia
and
Low-Beer, Naomi
and
Bello, Fernando
}, year = {
2017
}, publisher = {
The Eurographics Association
}, ISBN = {
978-3-03868-032-1
}, DOI = {
10.2312/vriphys.20171087
} }
Citation
Collections