TILES-2018, a longitudinal physiologic and behavioral data set of hospital workers

Medientyp: E-Artikel
Titel: TILES-2018, a longitudinal physiologic and behavioral data set of hospital workers
Beteiligte: Mundnich, Karel; Booth, Brandon M.; L’Hommedieu, Michelle; Feng, Tiantian; Girault, Benjamin; L’Hommedieu, Justin; Wildman, Mackenzie; Skaaden, Sophia; Nadarajan, Amrutha; Villatte, Jennifer L.; Falk, Tiago H.; Lerman, Kristina; Ferrara, Emilio; Narayanan, Shrikanth
Erschienen: Springer Science and Business Media LLC, 2020
Erschienen in: Scientific Data
Sprache: Englisch
DOI: 10.1038/s41597-020-00655-3
ISSN: 2052-4463
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Beschreibung: <jats:title>Abstract</jats:title><jats:p>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 <jats:italic>n</jats:italic> = 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.</jats:p>
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