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Annals of Operations Research

, Volume 276, Issue 1–2, pp 137–153 | Cite as

Data-driven combinatorial optimization for sensor-based assessment of near falls

  • Alla R. KammerdinerEmail author
  • Andre N. Guererro
Computational Biomedicine

Abstract

Falls represent a considerable public health problem, especially in older population. We describe and evaluate data-driven operations research models for detection and situational assessment of falls and near falls with a system of wearable sensors. The models are formulated as instances of the multidimensional assignment problem. Our computational studies provide some initial empirical evidence of the potential usefulness of this new application of the multidimensional assignment problem.

Keywords

The multidimensional assignment problem Falls and near falls Systems of wearable sensors 

Notes

Acknowledgements

The authors gratefully acknowledge the support from the National Science Foundation grant EEC-1342415.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.New Mexico State UniversityLas CrucesUSA

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