Semi-Automated Tracking: A Balanced Approach for Self-Monitoring Applications

@article{Choe2017SemiAutomatedTA,
  title={Semi-Automated Tracking: A Balanced Approach for Self-Monitoring Applications},
  author={Eun Kyoung Choe and Saeed Abdullah and Mashfiqui Rabbi and Edison Thomaz and Daniel A. Epstein and Felicia Cordeiro and Matthew Kay and Gregory D. Abowd and Tanzeem Choudhury and James Fogarty and Bongshin Lee and Mark Matthews and Julie A. Kientz},
  journal={IEEE Pervasive Computing},
  year={2017},
  volume={16},
  pages={74-84}
}
The authors present an approach for designing self-monitoring technology called "semi-automated tracking," which combines both manual and automated data collection methods. Through this approach, they aim to lower the capture burdens, collect data that is typically hard to track automatically, and promote awareness to help people achieve their self-monitoring goals. They first specify three design considerations for semi-automated tracking: data capture feasibility, the purpose of self… CONTINUE READING

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