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||Sensors and Software for Real-Time Activity Recognition on Mobile Phones
The goal of this open source project is to create software and hardware that permits automatic, 24/7 physical activity and context detection on common mobile phones. We are doing this by iteratively designing and testing Wockets -- miniature, low-cost hardware devices that will measure human motion using accelerometers. Wockets will send data to mobile phones that are processed by software running on the phone to automatically detect type, duration and intensity of physical activity.
The software that uses Wockets will be free and open source. The Wockets hardware will be collaboratively designed for low cost, robust operation; all the designs will be freely available, and we will do all we can to make it easy for researchers, hobbyists, and developers to get access to them.
This project is a collaboration between the Northeastern University Personal Health Informatics program, MIT House_n, and the Stanford Prevention Research Center. The work is funded by the NIH's GEI Exposure Biology Program. Although the medical community is interested in these sensors for long-term health monitoring (see our abstract), our goal is to foster the development of a much wider community of people interested in doing important, interesting, or just plain fun things with mobile phones that can automatically detect physical activities in real time.
To receive occasional updates on the project, please join the project mailing list.