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Expert System for Simulating and Predicting Sleep and Alertness Patterns

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2773))

Abstract

The Expert System ”Circadian Alertness Simulator” predicts employee sleep and alertness patterns in 24/7-work environments using rules of complex interactions between human physiology, operational demands and environmental conditions. The system can be tailored to the specific biological characteristics of individuals as well as to specific characteristics of groups of individuals (e.g., transportation employees). This adaptation capability of the system is achieved through a built-in learning module, which allows transferring information from actual data on sleep-wake-work patterns and individual sleep characteristics into an internal knowledge database. The expert system can be used as a fatigue management tool for minimizing the detrimental biological effects of 24-hour operations by providing feedback and advice for work scheduling and/or individual-specific lifestyle training. Consequently, it can help reduce accident risk and human-related costs of the 24/7 economy.

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References

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  3. Moore-Ede, M., Heitmann, A., Dean, C., Guttkuhn, R., Aguirre, A., Trutschel, U.: Circadian Alertness Simulator for Fatigue Risk Assessment in Transportation: Application to Reduce Frequency and Severity of Truck Accidents. Aviation, Space and Environmental Medicine (2003) (in press)

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Author information

Authors and Affiliations

  1. Circadian Technologies, Inc., 24 Hartwell Avenue, Lexington, MA, 02421, USA

    Udo Trutschel, Rainer Guttkuhn, Anneke Heitmann, Acacia Aguirre & Martin Moore-Ede

Authors
  1. Udo Trutschel
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  2. Rainer Guttkuhn
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  3. Anneke Heitmann
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  4. Acacia Aguirre
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  5. Martin Moore-Ede
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Editor information

Editors and Affiliations

  1. Computing Laboratory, Oxford University, Parks Road, OXI 3QD, United Kingdom

    Vasile Palade

  2. Intelligent Systems and Signal Processing Labs, Moulsecoomb, University of Brighton, BN2 4GJ, Brighton, United Kingdom

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, Mawson Lakes, University of South Australia, 5095, Adelaide, SA, Australia

    Lakhmi Jain

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© 2003 Springer-Verlag Berlin Heidelberg

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Cite this paper

Trutschel, U., Guttkuhn, R., Heitmann, A., Aguirre, A., Moore-Ede, M. (2003). Expert System for Simulating and Predicting Sleep and Alertness Patterns. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_17

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  • DOI: https://doi.org/10.1007/978-3-540-45224-9_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40803-1

  • Online ISBN: 978-3-540-45224-9

  • eBook Packages: Springer Book Archive

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