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      Investigating Wearable Technology for Fatigue Identification in the Workplace

      Griffiths, Christopher John Gilder; Bowen, Judy; Hinze, Annika
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      GrBH17_Final.pdf
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      DOI
       10.1007/978-3-319-67684-5_22
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      Griffiths, C. J. G., Bowen, J., & Hinze, A. (2017). Investigating Wearable Technology for Fatigue Identification in the Workplace. In R. Bernhaupt, G. Dalvi, A. Joshi, D. K. Balkrishan, J. O’Neill, & M. Winckler (Eds.), Human-Computer Interaction - INTERACT 2017 (Vol. 10514, pp. 370–380). Indian Inst Technol, Mumbai, INDIA: Springer. https://doi.org/10.1007/978-3-319-67684-5_22
      Permanent Research Commons link: https://hdl.handle.net/10289/12966
      Abstract
      Fatigue has been identified as a significant contributor to workplace accident rates. However, risk minimisation is a process largely based on self-reporting methodologies, which are not suitable for fatigue identification in high risk industries. Wearable technology which is capable of collecting physiological data such as step and heart rates as an individual performs workplace tasks has been proposed as a possible solution. Such devices are minimally intrusive to the individual and so can be used throughout the working day. Much is promised by the providers of such technology, but it is unclear how suitable it is for in-situ measurements in real-world work scenarios. To investigate this, we performed a series of studies designed to capture physiological and psychological data under differing (physical and mental) loading types with the intention of finding out how suitable such equipment is. Using reaction time (simple and choice) as a measure of performance we found similar correlations exist between loading duration and our measured indicators as those found in large-scale laboratory studies using state of the art equipment. Our results suggest that commercially available activity monitors are capable of collecting meaningful data in workplaces and are, therefore, worth investigating further for this purpose.
      Date
      2017
      Type
      Conference Contribution
      Publisher
      Springer
      Rights
      © IFIP International Federation for Information Processing 2017.This is the author's accepted version. The final publication is available at Springer via dx.doi.org/10.1007/978-3-319-67684-5_22
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      • Computing and Mathematical Sciences Papers [1385]
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