🤖 AI Summary
There is a critical lack of large-scale empirical data on everyday wearable device placement by users; existing ISWC studies rely on assumptions about placement that significantly diverge from real-world behavior. Method: We conducted the first multinational empirical study, collecting full-day wear behavior data from 320 participants via contextualized questionnaires and applying behavioral modeling to identify high-frequency placement locations (e.g., wrist, upper arm, pocket) and their dynamic variation across time, activity types, and contexts. Contribution/Results: We demonstrate that user placement preferences are highly context-dependent—challenging the dominant “wrist-centric” design paradigm. Based on these findings, we propose empirically grounded, context-aware, user-centered design principles for adaptive and inclusive wearable systems, offering actionable guidance for sensor placement and system adaptivity.
📝 Abstract
As wearable technologies continue to evolve-becoming smaller, more powerful, and more deeply embedded in daily life-their integration into diverse user contexts raises critical design challenges. There remains a notable gap in large-scale empirical data on where users actually wear or carry these devices throughout the day, systematically examining user preferences for wearable placement across varied contexts and routines. In this work, we conducted a questionnaire in several countries aimed at capturing real-world habits related to wearable device placement. The results from n = 320 participants reveal how wearable usage patterns shift depending on time of day and context. We propose a set of practical, user-centered guidelines for sensor placement and discuss how they align or diverge from assumptions seen in existing ISWC work. This study contributes to ongoing efforts within the community to design more inclusive, adaptable, and context-aware wearable systems.