WellBeat: A Framework for Tracking Daily Well-Being Using Smartwatches
| Autor: | Sungkyu Park, Luca Maria Aiello, Paul van Gent, Daniele Quercia, Marios Constantinides |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer Networks and Communications
Computer science Remote patient monitoring business.industry Zombie Wearable computer 020206 networking & telecommunications 02 engineering and technology Smartwatch Robustness (computer science) Human–computer interaction Well-being 0202 electrical engineering electronic engineering information engineering Heart rate variability The Internet business |
| Zdroj: | IEEE Internet Computing. 24:10-17 |
| ISSN: | 1941-0131 1089-7801 |
| DOI: | 10.1109/mic.2020.3017867 |
| Popis: | Human physiology is a window to our physical, mental, and emotional states; our well-being. Today, a new wave of objective data derived from consumer grade body sensors—like those equipped by smartwatches—paves the way toward a new approach in how well-being is being measured, continuously and unobtrusively. Here, we developed a framework for collecting and analyzing physiological data using smartwatches in-the-wild, and demonstrated its robustness in data obtained away from controlled laboratory settings. We found that changes in people's heart rate and heart rate variability are predictive not of momentary well-being (a scientific idea that continues to live on in the absence of in-the-wild evidence, aka, zombie theory) but of daily well-being. |
| Databáze: | OpenAIRE |
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