Understanding Ambulatory and Wearable Data for Health and Wellness
Name
Picard_Understanding ambulatory.pdf
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648.83 KB
Format
Adobe PDF
Checksum (MD5)
5565341d4d3da73aba07d8e4eb1f2bb2
Author(s)
Sano, Akane
Picard, Rosalind W.
Date Issued
March 2014
Journal
Proceedings of the 2014 AAAI Spring Symposium Series
Publisher
Association for the Advancement of Artificial Intelligence
Citation
Sano, Akane, and Rosalind W. Picard. "Understanding Ambulatory and Wearable Data for Health and Wellness." Proceedings of the 2014 AAAI Spring Symposium Series (March 2014).
Version
Author's final manuscript
Abstract
In our research, we aim (1) to recognize human internal states and behaviors (stress level, mood and sleep behaviors etc), (2) to reveal which features in which data can work as predictors and (3) to use them for intervention. We collect multi-modal (physiological, behavioral, environmental, and social) ambulatory data using wearable sensors and mobile phones, combining with standardized questionnaires and data measured in the laboratory. In this paper, we introduce our approach and some of our projects.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://www.aaai.org/ocs/index.php/SSS/SSS14/paper/viewFile/7708/7784
