Abstract: Medication non-adherence is a major healthcare challenge globally, with over half of patients with chronic conditions in developed countries failing to follow their prescribed medication regimen. This can lead to poor disease outcomes, increased hospital visits, and a significant financial burden on healthcare systems [1]. These issues have driven a recent wave of research, including the development of smart adherence products [6] that can be incorporated into a patient’s daily life to monitor medication adherence. In this work, we present a radar-based system for user identification while taking medication, which extends our recent work [5]. we conducted preliminary experiments examining semi-medication-taking activities executed by 6 subjects. Our system achieved 80% accuracy in identifying who has taken the medication in a group of 3 subjects.
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