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.
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Sounds of Health: Using Personalized Sonification Models to Communicate Health Information
This paper explores the feasibility of using sonification in delivering and communicating health and wellness status on personal devices. Ambient displays have proven to inform users of their health and wellness and help them to make healthier decisions, yet, little technology provides health assessments through sounds, which can be even more pervasive than visual displays. We developed a method to generate music from user preferences and evaluated it in a two-step user study. In the first step, we acquired general healthiness impressions from each user. In the second step, we generated customized melodies from music preferences in the first step to capture participants' perceived healthiness of those melodies. We deployed our surveys for 55 participants to complete on their own over 31 days. We analyzed the data to understand commonalities and differences in users' perceptions of music as an expression of health. Our findings show the existence of clear associations between perceived healthiness and different music features. We provide useful insights into how different musical features impact the perceived healthiness of music, how perceptions of healthiness vary between users, what trends exist between users' impressions, and what influences (or does not influence) a user's perception of healthiness in a melody. Overall, our results indicate validity in presenting health data through personalized music models. The findings can inform the design of behavior management applications on personal and ubiquitous devices.
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- NSF-PAR ID:
- 10451242
- Date Published:
- Journal Name:
- Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
- Volume:
- 6
- Issue:
- 4
- ISSN:
- 2474-9567
- Page Range / eLocation ID:
- 1 to 31
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3570346
