all AI news
A Matter of Annotation: An Empirical Study on In Situ and Self-Recall Activity Annotations from Wearable Sensors
March 18, 2024, 4:42 a.m. | Alexander Hoelzemann, Kristof Van Laerhoven
cs.LG updates on arXiv.org arxiv.org
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
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Global Data Architect, AVP - State Street Global Advisors
@ State Street | Boston, Massachusetts
Data Engineer
@ NTT DATA | Pune, MH, IN