Abstract
In this research a prototype of a virtual assistant mobile application, called Therapy Tracker is introduced. The application detects and captures prescription information and provides automated assistance in scheduling, reminding and tracking medications by keeping a list of medications, dosages, refill information, and prescription documentation. Despite the rapid growth and recent successes, creating such auto-assistant systems remains a challenging task. Augmented Reality technologies are used in our app to provide virtual information that combines real world situations, such as detecting and highlighting the correct medication from a group. The virtual assistant also guides the user through both visual and auditory alerts. In this paper we present Therapy Tracker, the interface design, architectural framework we designed and developed to support the system, and the results of a usability study conducted from real field studies. Our system was tested with 30 participants and achieved a mean SUS usability score of 84.5% (high).
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Notes
- 1.
SUS positive rated items: Item I1: “I think that I would like to use this system frequently” Item I3: “I thought the system was easy to use”, Item I5: “I found the various functions in this system were well integrated” Item I7 “I would imagine that most people would learn to use this system very quickly” Item I9: “I felt very confident using the system.”.
- 2.
SUS negative rated items: Item I2: “I found the system unnecessarily complex” Item I4: “I think that I would need the support of a technical person to be able to use this system”, Item I6: “I thought there was too much inconsistency in this system” Item I8 “I found the system very cumbersome to use” Item I10: “I needed to learn a lot of things before I could get going with this system.”.
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Sykes, E.R., Tofighi, G., Wang, Y., Ganguly, D., Janwaar, A., Singh, A. (2022). On the Design of Therapy Tracker: A Cross-platform Medication Management Application with Augmented Reality and Machine Learning. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2021, Volume 1. FTC 2021. Lecture Notes in Networks and Systems, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-030-89906-6_3
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