Abstract
Smartwatches enable not only the continuous collection of but also ubiquitous access to personal health data. However, exploring this data in-situ on a smartwatch is often reserved for singular and generic metrics, without the capacity for further insight. To address our limited knowledge surrounding smartwatch data exploration needs, we collect and characterize desired personal health data queries from smartwatch users. We conducted a week-long study (N = 18), providing participants with an application for recording responses that contain their query and current activity related information, throughout their daily lives. From the responses, we curated a dataset of 205 natural language queries. Upon analysis, we highlight a new preemptive and proactive data insight category, an activity-based lens for data exploration, and see the desired use of a smartwatch for data exploration throughout daily life. To aid in future research and the development of smartwatch health applications, we contribute the dataset and discuss implications of our findings.
Original language | English |
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Article number | 179 |
Journal | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies |
Volume | 6 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2023 Jan 11 |
Bibliographical note
Publisher Copyright:© 2023 ACM.
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Hardware and Architecture
- Computer Networks and Communications