Understanding ambulatory and wearable data for health and wellness

Akane Sano, Rosalind W. Picard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationBig Data Becomes Personal
Subtitle of host publicationKnowledge into Meaning - Papers from the AAAI Spring Symposium, Technical Report
PublisherAI Access Foundation
Number of pages2
ISBN (Print)9781577356547
StatePublished - 2014
Event2014 AAAI Spring Symposium - Palo Alto, CA, United States
Duration: Mar 24 2014Mar 26 2014

Publication series

NameAAAI Spring Symposium - Technical Report


Conference2014 AAAI Spring Symposium
Country/TerritoryUnited States
CityPalo Alto, CA

ASJC Scopus subject areas

  • Artificial Intelligence


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