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ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2025,12,2]]},"abstract":"<jats:p>High-quality labels of activity data with broad representations and real-world variability are key to developing activity recognition models tailored to the needs and characteristics of older adults. However, labeling real-world data presents significant challenges, placing a heavy burden on users to provide high-quality labels while staying engaged in their activities. This paper investigates older adults' perceptions of providing high-quality labels in the context of training their personalized activity trackers. We conducted a co-design study with 12 older adults to envision the labeling process\u2014describing activity names and time spans\u2014using the teachable machines paradigm as a scaffold. We unpack the contextualized definitions of accuracy, precision, and granularity through a thematic analysis of older adults' perspectives on activity labeling. Our findings present participants' preferred strategies for obtaining high-quality activity labels with less burden and intrusiveness, including user-initiated labeling and machine-initiated prompting. We discuss design considerations for future data labeling tools that address discrepancies between user perceptions and technical standards in training personalized activity trackers.<\/jats:p>","DOI":"10.1145\/3770649","type":"journal-article","created":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T19:42:32Z","timestamp":1764704552000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Enabling Older Adults to Provide High-quality Activity Labels: Unpacking Accuracy, Precision, and Granularity in Activity Labeling"],"prefix":"10.1145","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1234-7621","authenticated-orcid":false,"given":"Yiwen","family":"Wang","sequence":"first","affiliation":[{"name":"College of Information, University of Maryland, College Park, Maryland, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4485-9322","authenticated-orcid":false,"given":"Hossein","family":"Khayami","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4217-627X","authenticated-orcid":false,"given":"Bongshin","family":"Lee","sequence":"additional","affiliation":[{"name":"Yonsei University, Seoul, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8110-4239","authenticated-orcid":false,"given":"Amanda","family":"Lazar","sequence":"additional","affiliation":[{"name":"College of Information, University of Maryland, College Park, Maryland, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7798-308X","authenticated-orcid":false,"given":"Hernisa","family":"Kacorri","sequence":"additional","affiliation":[{"name":"College of Information, University of Maryland, College Park, Maryland, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5038-8320","authenticated-orcid":false,"given":"Eun Kyoung","family":"Choe","sequence":"additional","affiliation":[{"name":"College of Information, University of Maryland, College Park, Maryland, USA"}]}],"member":"320","published-online":{"date-parts":[[2025,12,2]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). 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