Multiple sclerosis image-guided subcutaneous injections using augmented reality guided imagery

ABSTRACT

In this paper, we explore how new technologies can be used to improve Multiple Sclerosis (MS) treatments. Treatment of MS most often includes self-injecting medicine into the subcutis, the tissue layer between the skin and the muscle. The injections can make a patient’s skin sore, red, itchy, and even cause pain, thus many patients suffer from injection anxiety. The aim of our work is to determine whether an application based on augmented reality (AR) technology can help reduce patients’ injection anxiety and perceived pain during the administration of their medication. An AR application, MSease, that allows MS patients to visualise injection sites with the help of an overlaid AR grid which also serves to keep track of their previous injections, was developed. An MS patient and people without MS were consulted in order to assess the quality of the application. The results of this research indicate a marked reduction in injection anxiety and a minor reduction in perceived pain when using our application.

KEYWORDS:

• Augmented reality
• multiple Sclerosis
• injection anxiety
• perceived pain
• image-guidance
• subcutaneous injections
• mHealth

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Natural Sciences and Engineering Research Council of Canada [RGPIN-2017-06722].

Notes on contributors

Donya Meshgin

Donya Meshgin is an undergraduate software engineering student in the Real-time, Embedded and Avionics software program option at Concordia University (Montreal, Canada). In 2020, she worked as a research assistant at the Applied Perception Lab at Concordia University, receiving an Undergraduate Student Research Award. Her research interests include applications of augmented reality and virtual reality for guided imagery.

Marta Kersten-Oertel

Marta Kersten-Oertel received a BSc (Honours) degree in Computer Science and a BA degree in Art History from Queen’s University (Kingston) in 2002. In 2005 she completed her MSc in Computer Science at Queen’s University. After working as a research assistant at the GRaphisch-Interaktive Systeme at the University of Tübingen (Germany), in 2015 she received a PhD degree in Biomedical Engineering at McGill University (Montreal). Since 2016, she has been an Assistant Professor in Computer Science and Software Engineering, PERFORM Centre researcher and is currently the Concordia University Research Chair in Applied Perception. Her research is focused on developing and evaluating new visualization techniques, mixed reality displays, and interaction methods in health and clinical applications.