CareCam: An Intelligent, Camera-Based Health Companion at the Workplace

被引:5
作者
Kraft, Dimitri [1 ]
Schmidt, Angelina [2 ]
Oschinsky, Frederike Marie [1 ]
Buettner, Lea [1 ]
Lambusch, Fabienne [2 ]
Van Laerhoven, Kristof [3 ]
Bieber, Gerald [1 ]
Fellmann, Michael [2 ]
机构
[1] Fraunhofer IGD, Rostock, Germany
[2] Univ Rostock, Rostock, Germany
[3] Univ Siegen, Siegen, Germany
来源
INFORMATION SYSTEMS AND NEUROSCIENCE, NEUROIS RETREAT 2022 | 2022年 / 58卷
关键词
Imaging photoplethysmography; Pose estimation; Machine learning; Computer vision; Facial expression recognition; Multi-modal approach; Workplace health; Workplace assistance; METABOLIC RISK; TIME; STRESS; WORK;
D O I
10.1007/978-3-031-13064-9_16
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Health assistant tools at the workplace may contribute to preventing workrelated 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.
引用
收藏
页码:155 / 161
页数:7
相关论文
共 23 条
  • [1] Sit-Stand Workstations A Pilot Intervention to Reduce Office Sitting Time
    Alkhajah, Taleb A.
    Reeves, Marina M.
    Eakin, Elizabeth G.
    Winkler, Elisabeth A. H.
    Owen, Neville
    Healy, Genevieve N.
    [J]. AMERICAN JOURNAL OF PREVENTIVE MEDICINE, 2012, 43 (03) : 298 - 303
  • [2] Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
    Barsoum, Emad
    Zhang, Cha
    Ferrer, Cristian Canton
    Zhang, Zhengyou
    [J]. ICMI'16: PROCEEDINGS OF THE 18TH ACM INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, 2016, : 279 - 283
  • [3] Bazarevsky V, 2020, Arxiv, DOI [arXiv:2006.10204, DOI 10.48550/ARXIV.2006.10204]
  • [4] New Methods for Stress Assessment and Monitoring at the Workplace
    Carneiro, Davide
    Novais, Paulo
    Augusto, Juan Carlos
    Payne, Nicola
    [J]. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, 2019, 10 (02) : 237 - 254
  • [5] Mindfulness Training Reduces Stress at Work: a Randomized Controlled Trial
    Chin, Brian
    Slutsky, Jerry
    Raye, Julianna
    Creswell, John David
    [J]. MINDFULNESS, 2019, 10 (04) : 627 - 638
  • [6] Reconstructing QRS Complex From PPG by Transformed Attentional Neural Networks
    Chiu, Hong-Yu
    Shuai, Hong-Han
    Chao, Paul C. -P.
    [J]. IEEE SENSORS JOURNAL, 2020, 20 (20) : 12374 - 12383
  • [7] Finding the Right Fit: Understanding Health Tracking in Workplace Wellness Programs
    Chung, Chia-Fang
    Gorm, Nanna
    Shklovski, Irina
    Munson, Sean A.
    [J]. PROCEEDINGS OF THE 2017 ACM SIGCHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'17), 2017, : 4875 - 4886
  • [8] Dratva J., 2020, AUSWIRKUNGEN SPORT B
  • [9] Fitbit Activity Trackers Interrupt Workplace Sedentary Behavior A New Application
    Guitar, N. A.
    MacDougall, A.
    Connelly, D. M.
    Knight, E.
    [J]. WORKPLACE HEALTH & SAFETY, 2018, 66 (05) : 218 - 222
  • [10] Haescher M, 2020, INT CONF ACOUST SPEE, P4122, DOI [10.1109/icassp40776.2020.9053130, 10.1109/ICASSP40776.2020.9053130]