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92441 |
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|a Sano, Akane
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|a Massachusetts Institute of Technology. Media Laboratory
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|a Program in Media Arts and Sciences
|q (Massachusetts Institute of Technology)
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|a Sano, Akane
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|a Picard, Rosalind W.
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|a Picard, Rosalind W.
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|a Understanding Ambulatory and Wearable Data for Health and Wellness
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|b Association for the Advancement of Artificial Intelligence,
|c 2014-12-22T18:33:37Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/92441
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|a 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.
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|a en_US
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|a Article
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|t Proceedings of the 2014 AAAI Spring Symposium Series
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