CareCam: An Intelligent, Camera-Based Health Companion at the Workplace
Dimitri Kraft (),
Angelina Schmidt (),
Frederike Marie Oschinsky (),
Lea Büttner (),
Fabienne Lambusch (),
Kristof Laerhoven (),
Gerald Bieber () and
Michael Fellmann ()
Additional contact information
Dimitri Kraft: Fraunhofer IGD
Angelina Schmidt: University of Rostock
Frederike Marie Oschinsky: Fraunhofer IGD
Lea Büttner: Fraunhofer IGD
Fabienne Lambusch: University of Rostock
Kristof Laerhoven: University of Siegen
Gerald Bieber: Fraunhofer IGD
Michael Fellmann: University of Rostock
A chapter in Information Systems and Neuroscience, 2022, pp 155-161 from Springer
Abstract:
Abstract Health assistant tools at the workplace may contribute to preventing work-related absenteeism, increasing overall employee satisfaction, and reducing the costs of sickness or presenteeism in the long term. The tools may be integrated into a digital corporate health management strategy. Despite their huge potential, a major drawback of common tools (e.g., wearables, dedicated cameras) are that they require direct interaction, skin contact, or come with a high acquisition cost. A concept for unobtrusive and software-based monitoring to increase long-term health, improve working conditions or show the necessary adjustments to the new work situation can help to solve these problems. This paper presents a concept that shows how a simple webcam can be utilized to record vital signs, posture, and behavior during working hours. It offers individual and intelligent interventions and recommendations based on these data to reduce psychological and physical stress. Our approach demonstrates that the required parameters can be used to offer user-tailored interventions based on simple rules. We present a prototypical implementation of an intelligent health companion and show avenues for future research.
Keywords: Imaging photoplethysmography; Pose estimation; Machine learning; Computer vision; Facial expression recognition; Multi-modal approach; Workplace health; Workplace assistance (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-031-13064-9_16
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DOI: 10.1007/978-3-031-13064-9_16
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