Data Driven Wellness: From Self-Tracking to Behavior Change
Papers from the 2013 AAAI Spring Symposium
Takashi Kido, Keiki Takadama Program Cochairs
This reportm focuses on data driven wellness which derives behavior change from our daily life starting from self tracking of our health. For example, when we know our genome information (for example, a possibility of being diabetes) from our saliva (that is, self tracking), our mind changes to not eat high-calorie foods or to start running to keep or lose our weight (that is, behavior change). Such an important stream of improving our health is promoted owing to a lot of data of our health (that is, data driven wellness) acquired by current technologies (for example, calories calculation by smart phone), and these streams contribute to creating society or social activities on health improvement (for example, society or social activities that supports diabetes patients). The papers in this report explore such AI technologies and discuss possible solutions for our wellness.