Abstract
Occupational Heat Stress (OHS) happens when a worker is physically active in hot environments. OHS can produce a strain on the body which leads to discomfort and eventually to heat illness and even death. Related ISO standards contain methods to estimate OHS and to ensure the safety and health of workers, but, they are subjective, impersonal, performed a posteriori, and even invasive. We hypothesize that a real time automated method is more effective and objective estimating OHS if it fuses data from environmental sensors, unobtrusive physiological body sensors, and takes into account the user profile. We propose a personalized method based on ergonomic calculations to offer a solution. We found that our method allows estimating the personalized effort levels, energy expenditure and drudgery of work for each worker and enables to take informed decisions to control OHS. We think that ISO standards could consider technological advances to propose real-time personalized methods.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Koskimaki, H., Huikari, V.: Activity recognition using a wrist-worn inertial measurement unit: A case study for industrial assembly lines. In: MED 2009 (2009)
Migliaccio, G., Teizer, J., Cheng, T., Gatti, U.: Automatic Identification of Unsafe Bending Behavior of Construction Workers Using Real-Time Location Sensing and Physiological Status Monitoring. In: Proceedings of Construction Research Congress 2012, pp. 633–642 (2012)
Senyurek, L., Hocaoglu, K., Sezer, B., Urhan, O.: Monitoring workers through wearable transceivers for improving work safety. In: 2011 IEEE 7th Int. Symp. Intell. Signal Processing, pp. 1–3 (2011)
Gatti, U., Migliaccio, G., Bogus, S., Schneider, S.: Using Wearable Physiological Status Monitors for Analyzing the Physical Strain-Productivity Relationship for Construction Tasks. Bridges 10 (2014)
Cho, J., Kim, J., Kim, T.: Smart Phone-based Human Activity Classification and Energy Expenditure Generation in Building Environments, Seoul, Korea (2012)
Ainsworth, B.E., Haskell, W.L., Whitt, M.C., Irwin, M.L.: Compendium of Physical Activities: an update of activity codes and MET intensities. Medicine & Science in Sports & Exercise (2000)
Callejon-Ferre, A.: Improving the climate safety of workers in Almería-type greenhouses in Spain by predicting the periods when they are most likely to suffer thermal stress. Applied Ergonomy (2011)
Marucci, A., Pagniello, B., Monarca, D., Colantoni, A., Biondi, P., Cecchini, M., et al.: The heat stress for workers during vegetable grafting in greenhouses. In: International Conference RAGUSA SHWA 2012, pp. 321–328 (2008, 2012)
Rednic, R., Kemp, J., Gaura, E., Brusey, J.: Networked Body Sensing: Enabling real-time decisions in health and defence applications. In: ICACSIS 2011 (2011)
Reinert, D., Flaspöler, E., Hauke, A.: Identification of emerging occupational safety and health risks. Safety Science Monitoring 3 (2007)
Curone, D., Secco, E.L., Tognetti, A., Magenes, G.: An Activity Classifier based on Heart Rate and Accelerometer Data Fusion. International Journal of Bioelectromagnetism 15(1), 7–12 (2013)
Frimat, P., Amphoux, M., Chamoux, A.: Interprétation et measure de la fréquence cardiaque. Revue de Médicine du Travail XV(4), 147–165 (1988)
American College of Sports Medicine. Prevention of thermal injuries during distance running - Position Stand. The Medical Journal of Australia 141(12-13), 876–879 (1984)
Tao, C., Miglaccio, G., Teizer, J., Gatti, U.: Data Fusion of Real-Time Location Sensing and Physiological Status Monitoring for Ergonomics Analysis of Construction Workers. Journal of Computing in Civil Engineering 27(3), 320–335 (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Pancardo, P., Acosta Escalante, F.D., Hernández-Nolasco, J.A., Wister, M.A., López-de-Ipiña, D. (2014). A Sensor-Based Method for Occupational Heat Stress Estimation. In: Hervás, R., Lee, S., Nugent, C., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services. UCAmI 2014. Lecture Notes in Computer Science, vol 8867. Springer, Cham. https://doi.org/10.1007/978-3-319-13102-3_41
Download citation
DOI: https://doi.org/10.1007/978-3-319-13102-3_41
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13101-6
Online ISBN: 978-3-319-13102-3
eBook Packages: Computer ScienceComputer Science (R0)