This project is to design, develop, and evaluate an innovative family routine sensing and feedback system called FRESH (Family Routine, Education, and Sensing Health), which empowers families to actively engage in preventing child obesity and improving family wellness. We develop unobtrusive sensing system using audio, motion, and light sensors from off-the-shelf mobile devices (e.g., Tablet personal computer (PC), smartphone). Integrated with an off-the-shelf wearable physical activity detection device, our system will detect screen viewing duration, family dinner dynamic, sleep quality and duration, and physical activity level of the child. The tablet PC will display collected sensor data through virtual pet and visual metaphors such as a blossoming flower or a growing plant. The family's progress toward improved routine will be reflected through the virtual pet and visual metaphors, which will be available in the periphery of the family's activities throughout the day (e.g., displayed in the living room, parents' smartphone home screen). Families will receive automated feedback and suggestions for improving their routine. Family members will also see how other families are doing compared to them for encouragement and insights. We plan to engage K-12 students during summer to play with the demonstration of our project, increase motivation for scientific research, and increase awareness of family wellness to the surrounding communities. Our technology will be shared as an open-source after the completion of the project for broader dissemination and development of the science we have developed from our project. Overall, our project develops new methods and paradigms of clinical support that engage all family members and a community of families in improving child and family health.

The goal of this project is to design and evaluate the FRESH system, which automatically senses family routine and gives motivational feedback to help families improve daily routines for child obesity prevention. Family routines, such as sleep, screen viewing, family dinner, and physical activity, are critical predictors of child obesity. While many mobile health devices focused on motivating individuals to pursue healthy behaviors, systems that take a family- and sensor-based approach have been under explored. No existing technologies sense family routines critical to child obesity. With visual and textual feedback driven by sensor data on routines, FRESH offers an engaging way for the children, the family, and the community to involve in family wellness. The technical merits of the project includes: (1) Develop and evaluate unobtrusive sensing technology for monitoring family routines; (2) Formatively assess designing visual and textual feedback in the FRESH system; (3) Evaluate the feasibility and acceptability of the system deployment. To fulfill the objective, we will use participatory design, interviews, diaries, field studies, experiments, and user log analysis.

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University of California San Diego
La Jolla
United States
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