Abstract
Public health trends are currently monitored and diagnosed based on large studies that often rely on pen-and-paper data methods that tend to require a large collection campaign. With the pervasiveness of smart-phones and -watches throughout the general population, we argue in this paper that such devices and their built-in sensors can be used to capture such data more accurately with less of an effort. We present a system that targets a pan-European and harmonised architecture, using smartphones and wrist-worn activity loggers to enable the collection of data to estimate sedentary behavior and physical activity, plus the consumption of sugar-sweetened beverages. We report on a unified pilot study across three countries and four cities (with different languages, locale formats, and data security and privacy laws) in which 83 volunteers were asked to log beverages consumption along with a series of surveys and longitudinal accelerometer data. Our system is evaluated in terms of compliance, obtained data, and first analyses.
Original language | English |
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Title of host publication | Proceedings of the 4th international Workshop on Sensor-Based Activity Recognition and Interaction |
Subtitle of host publication | iWOAR 2017 |
Editors | Kristina Yordanova, Max Schröder, Sebastian Bader, Thomas Kirste |
Publisher | Association for Computing Machinery |
ISBN (Electronic) | 9781450352239 |
DOIs | |
Publication status | Published - 21 Sept 2017 |
Event | 4th international Workshop on Sensor-Based Activity Recognition and Interaction, iWOAR 2017 - Rostock, Germany Duration: 21 Sept 2017 → 22 Sept 2017 |
Conference/symposium
Conference/symposium | 4th international Workshop on Sensor-Based Activity Recognition and Interaction, iWOAR 2017 |
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Country/Territory | Germany |
City | Rostock |
Period | 21/09/17 → 22/09/17 |
Keywords
- Activity recognition
- Barcode scanning
- Beverage consumption logging
- Multi-modal data collection
- Presentation