TILES-2018, a longitudinal physiologic and behavioral data set of hospital workers
Abstract
We present a novel longitudinal multimodal corpus of physiological and behavioral data collected from direct clinical providers in a hospital workplace. We designed the study to investigate the use of off-the-shelf wearable and environmental sensors to understand individual-specific constructs such as job performance, interpersonal interaction, and well-being of hospital workers over time in their natural day-to-day job settings. We collected behavioral and physiological data from n = 212 participants through Internet-of-Things Bluetooth data hubs, wearable sensors (including a wristband, a biometrics-tracking garment, a smartphone, and an audio-feature recorder), together with a battery of surveys to assess personality traits, behavioral states, job performance, and well-being over time. Besides the default use of the data set, we envision several novel research opportunities and potential applications, including multi-modal and multi-task behavioral modeling, authentication through biometrics, and privacy-aware and privacy-preserving machine learning.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 16, 2020
- Source ID
- 10.1038/s41597-020-00655-3
Entities
People
- Amrutha Nadarajan
- Benjamin Girault
- Brandon M Booth
- Emilio Ferrara
- Jennifer L. Villatte
- Justin L'Hommedieu
- Karel Mundnich
- Kristina Lerman
- Mackenzie Wildman
- Michelle L'Hommedieu
- Shrikanth Narayanan
- Sophia Skaaden
- Tiago Falk
- Tiantian Feng
Organizations
- Intelligence Advanced Research Projects Activity