Armbeta
Author(s) -
Lok Sum Lo,
James C. Galloway,
Bernd Ploderer,
Dimitri Perrin
Publication year - 2017
Publication title -
qut eprints (queensland university of technology)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/3152771.3156136
Subject(s) - computer science
The aim of this research is to create a simple wearable technology for people engaged in upper limb rehabilitation to track how much they move their arm as well as the activities that the arm is engaged in. This paper describes the design of the `ArmBeta' prototype, which is based on the Microsoft Band 2 device and a mobile app. A lab-based trial study of ArmBeta with four healthy adults showed the accuracy for recognising reach-and-retrieve tasks was 78%, but the accuracy for other tasks (opening doors, eating, stirring a pot) was below 50%. A consecutive two-hour trial in daily life showed that the information generated was easy to understand but that the accuracy and accessibility need to be improved. We discuss the trade-offs between accessibility, accuracy, and the significance of information generated to track arm movement. The paper closes with considerations for future work to refine the system and to engage with patients and clinicians involved in rehabilitation.
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