March 18, 2024, 4:42 a.m. | Alexander Hoelzemann, Kristof Van Laerhoven

cs.LG updates on arXiv.org arxiv.org

arXiv:2305.08752v2 Announce Type: replace-cross
Abstract: Research into the detection of human activities from wearable sensors is a highly active field, benefiting numerous applications, from ambulatory monitoring of healthcare patients via fitness coaching to streamlining manual work processes. We present an empirical study that compares 4 different commonly used annotation methods utilized in user studies that focus on in-the-wild data. These methods can be grouped in user-driven, in situ annotations - which are performed before or during the activity is recorded …

abstract annotation annotations applications arxiv coaching cs.hc cs.lg detection fitness healthcare human matter monitoring patients processes recall research sensors study type via wearable wearable sensors work

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