Public Health Assisting Smart Technologies (PHAST)

The mission of the PHAST is the creation of smart devices that promote awareness and understanding of personal activity spaces and how they affect health. Through the creation of wearable devices that integrate data-logging global positioning system receivers with personal and environmental sensors, our aim is to create integrated devices that can provide a wealth of individual-level data that can address major public health problems, such as the relationship between physical exercise and obesity, social interaction and the spread of infectious diseases, assessment of small-scale variations in exposures to airborne pollution, and environmental injustices. These devices allow for the spatial and temporal mapping of individual activity spaces and the identification of health risks associated with these spaces. Such information has the potential to improve Public Health by informing and promoting alternative environmental policies, community perspectives, and individual behaviors.

CalFit — Smartphone-based Physical Activity Tracking

 

 

 

 

 

 

Working with researchers from Electrical Engineering and Computer Science at Berkeley, we created CalFit, a smartphone application that tracks a user’s time-location and physical activity patterns.

CalFit showcases the latest research in energy expenditure and activity tracking algorithms developed through collaboration between UC Berkeley Engineering and the School of Public Health, and validated at UC Davis Medical Center.

CalFit was developed to be flexible, allowing for continuous addition of other components need for epidemiological research.  Some of these components include:

  • Ecological Momentary Assessment (EMA) for self-reported user outcomes
  • Dietary Assessment
  • Heart Rate Variability Sensors
  • Air Pollution Sensors
  • Social Networking and Gaming

CalFit is the latest evolution of ongoing research into Body Sensor Networks.  Our previous research included use of Internet Tablets as coordinators for various body worn sensors and small microprocessors (sensor motes).

 

 

We have demonstrated:

  • Body worn accelerometers for activity recognition
  • Wearable air pollution monitors for mapping individual and community-level air pollution
  • Combinations of wearable and home-based sensors, e.g., integration with blood pressure and digital scale for congestive heart failure applications.

 

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