The majority of studies (N = 26, 65%) used multi-sensor systems (incorporating > 1 wearable sensors), and accelerometers were the most commonly utilized sensor (N = 25, 62.5%). This scoping review included N = 40 studies (from 33 articles) that reported on one or more wearable sensors used to automatically detect eating activity in the field. Five databases were searched in December 2019, and 618 records were retrieved from the literature search. This scoping review summarizes the current use of wearable devices/sensors that automatically detect eating-related activity in naturalistic research settings.
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Objective measurement tools, specifically, wearable sensors, present the opportunity to minimize the major limitations of self-reported eating measures by generating supplementary sensor data that can improve the validity of self-report data in naturalistic settings. Our research contributes to a growing understanding of designing family centered health-informatics tools to support the combined needs of parents and children.ĭietary intake, eating behaviors, and context are important in chronic disease development, yet our ability to accurately assess these in research settings can be limited by biased traditional self-reporting tools. However, there were also moments when family members, in particular parents, felt discomfort from sharing their sleep and mood with other family members. Our results indicate that children can be active tracking contributors and that having parents and children track together encourages turn-taking and working together. This study uses a family systems perspective to explore research questions regarding the feasibility of children actively tracking health data alongside their parents and the effects of tracking and sharing on family dynamics. Ten families participated in the study probe between 15 and 50 days.
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We deployed DreamCatcher as a probe to examine the design space of tracking sleep as a family. DreamCatcher is an in-home, interactive, shared display that aggregates data from wrist-worn sleep sensors and self-reported mood.
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To examine how to design a family-centered sleep tracking tool, we designed DreamCatcher. Most sleep-tracking tools, however, are designed for adults and make it difficult for parents and children to track together. Parents and their school-age children can impact one another's sleep.
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Finally, we identify future research efforts related to designing for kids' self-tracking and collaborative tracking with parents. We discuss how our findings could inform the design of wearables that serve as more than monitoring devices, and instead support children and parents as equal stakeholders, providing implications for kids' agency, long-term development, and overall well-being. We found that many kids' wearables are technologically sophisticated devices that focus on parents' ability to communicate with their children and keep them safe, as well as encourage physical activity and nurture good habits. We collected rich data on the functionality of these devices and assessed how different features satisfy parents' information needs, and identified opportunities for wearables to support children's needs and interests.
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To gain insight into the current landscape of kids' wearables, we surveyed 47 wearable devices marketed for children. However, research on kids' wearables is sparse and often focuses on their use in the context of parental surveillance. Wearable devices hold great potential for promoting children's health and well-being.