Remote evaluation of augmented reality interaction with personal health information

Orit Shaer, Jennifer Otiono, Ziyue Qian, Ayanna Seals, Oded Nov

Research output: Contribution to journalArticlepeer-review

Abstract

This article discusses novel research methods used to examine how Augmented Reality (AR) can be utilized to present “omic” (i.e., genomes, microbiomes, pathogens, allergens) information to non-expert users. While existing research shows the potential of AR as a tool for personal health, methodological challenges pose a barrier to the ways in which AR research can be conducted. There is a growing need for new evaluation methods for AR systems, especially as remote testing becomes increasingly popular. In this article, we present two AR studies adapted for remote research environments in the context of personal health. The first study (n = 355) is a non-moderated remote study conducted using an AR web application to explore the effect of layering abstracted pathogens and mitigative behaviors on a user, on perceived risk perceptions, negative affect, and behavioral intentions. This study introduces methods that address participant precursor requirements, diversity of platforms for delivering the AR intervention, unsupervised setups, and verification of participation as instructed. The second study (n = 9) presents the design and moderated remote evaluation of a technology probe, a prototype of a novel AR tool that overlays simulated timely and actionable environmental omic data in participants' living environment, which helps users to contextualize and make sense of the data. Overall, the two studies contribute to the understanding of investigating AR as a tool for health behavior and interventions for remote, at-home, empirical studies.

Original languageEnglish (US)
Article number934694
JournalFrontiers in Computer Science
Volume4
DOIs
StatePublished - Aug 15 2022

Keywords

  • Mixed Reality
  • augmented reality
  • health behavior
  • human-computer interactions
  • remote MR research

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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