Data Glasses for Picking Workplaces

Impact on Physical Workloads
  • Daniel FriemertEmail author
  • Rolf Ellegast
  • Ulrich Hartmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9752)


In the field of logistics the interest in wearable computing devices is constantly growing. In earlier studies it has been shown that data glasses can be a powerful tool for optimising warehouse management processes. However, those studies exclusively dealt with the impact of smart glasses on the efficiency of labour whereas our approach focuses on investigating the influence of data glasses on physical workloads. For this purpose we have designed a simplified picking workplace that enables us to carry out motion analyses and the concurrent assessment of physiological parameters under lab conditions. In this article we present the key features of our picking machine and the tailor-made measurement protocols together with the adequate evaluation methods that are used to quantify the effects of smart glasses on the physical workloads imposed on the study subjects.


Data glasses Physical workload Posture Picking workplace 


  1. 1.
    Schwerdtfeger, B., Reif, R., Günthner, W., Klinker, G.: Pick-by-Vision: there is somehing to pick at the end of the augmented tunnel. Virtual Reality 15, 213–223 (2011)CrossRefGoogle Scholar
  2. 2.
    Reif, R., Walch, D.: Augmented & Virtual Reality applications in the field of logistics. Vis. Comput. Int. J. Comput. Graph. 24, 987–994 (2008)Google Scholar
  3. 3.
  4. 4.
    Information on the Volkswagen Webpage about a project using data glasses in logistics.
  5. 5.
    Theis, S., Pfendler, C., Alexander, T., Mertens, A., Brandl, C., Schlick, M.: Head-Mounted Displays - Bedingungen des sicheren und beanspruchungsoptimalen Einsatzes. Physische Beanspruchung beim Einsatz von HMDs. Bundesanstalt für Arbeitsschutz und Arbeitsmedizin (2015). ISBN: 978-3-88261-162-5Google Scholar
  6. 6.
    Ellegast, R., Hermanns, I., Schiefer, C.: Workload assessment in field using the ambulatory CUELA system. In: Duffy, V.G. (ed.) ICDHM 2009. LNCS, vol. 5620, pp. 221–226. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    Shum, H.P., Ho, E.S., Jiang, Y., Takagi, S.: Real-time posture reconstruction for Microsoft Kinect. IEEE Trans. Cybern. 43(5), 1357–1369 (2013)CrossRefGoogle Scholar
  8. 8.
    Hermens, H.J., Freriks, B.: The state of the art on sensors and sensor placement procedures for surface electromyography: a proposal for sensor placement procedures. Roessingh Research and Development, Enschede, The Netherlands (1997).
  9. 9.
    Peter, C., Ebert, E., Beikirch, H.: A wearable multi-sensor system for mobile acquisition of emotion-related physiological data. In: Tao, J., Tan, T., Picard, R.W. (eds.) ACII 2005. LNCS, vol. 3784, pp. 691–698. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  10. 10.
    Pantelopoulos, A., Bourbakis, N.G.: A survey on wearable sensor-based systems for health monitoring and prognosis. Syst. Man Cybern. Part C: IEEE Trans. Appl. Rev. 40(1), 1–12 (2010)CrossRefGoogle Scholar
  11. 11.
    Kuorinka, I., Jonsson, B., Kilbom, A.: Standardized Nordic questionnaires for the analysis of musculoskeletal symptoms. Appl. Ergon. 18, 233–237 (1987)CrossRefGoogle Scholar
  12. 12.
    Drury, C.G.: A biomechanical evaluation of the repetitive motion injury potential of industrial jobs. Semin. Occup. Med. 2, 41–49 (1987)Google Scholar
  13. 13.
    McAtamney, L., Corlett, E.N.: RULA: a survey method for the investigations of work-related upper limb disorders. Appl. Ergon. 24, 91–99 (1993)CrossRefGoogle Scholar
  14. 14.
    Hoehne-Hückstädt, U., Herda, C., Ellegast, R., Hermanns, I., Hamburger, R., Ditchen, D.: Muskel-Skelett-Erkrankungen der oberen Extremität und berufliche Tätigkeit. BGIA-Report 2/2007, Sankt Augustin: HVBG (2007)Google Scholar
  15. 15.
    Karhu, O., Kansi, P., Kuorinka, I.: Correcting working postures in industry: A practical method for analysis. Appl. Ergon. 8, 199–201 (1977)CrossRefGoogle Scholar
  16. 16.
    Ellegast, R.: Personengebundenes Messsystem zur automatisierten Erfassung von Wirbelsäulenbelastungen bei beruflichen Tätigkeiten. BIA-Report 5/98, Sankt Augustin: HVBG (1998).
  17. 17.
    Jäger, M., Luttmann, A., Göllner, R., Laurig, W.: Der Dortmunder - Biomechanische Modellbildung zur Bestimmung und Beurteilung der Belastung der Lendenwirbelsäule bei Lastenhandhabungen. In: Radandt, S., Grieshaber R., Schneider, W. (eds.) Prävention von arbeitsbedingten Gesundheitsgefahren und Erkrankungen, pp. 105–124 (2000)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Daniel Friemert
    • 1
    • 2
    Email author
  • Rolf Ellegast
    • 1
    • 2
  • Ulrich Hartmann
    • 2
  1. 1.Institute for Occupational Safety and Health of the German Social Accident InsuranceSt. AugustinGermany
  2. 2.Department of Mathematics and TechnologyUniversity of Applied Sciences KoblenzRemagenGermany

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