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Robust Network Models for using Mobility Parameters for Health Assessment

Authors:
Abhilash Patolla
Ik-Hyun Youn
Hesham Ali

Keywords: Mobility parameters; network models; Data analytics; Population based analysis; Health Assessment

Abstract:
With the recent development of wearable mobility devices, researchers are pressed to develop advanced models to take advantage of these devices. Although wearable devices produce a large volume of raw data, the process of extracting useful knowledge from the data collected from such devices remains limited. In particular, not as much has been established on how mobility parameters can be used to develop mobility patterns to assess health levels and predict potential health hazards. In this work, we develop a robust model, based on a population analysis, to utilize mobility data and extract useful information related to health assessment. We propose the use of correlation networks as one of population based analytics to consider variability and analyze mobility. The proposed approach aims at identifying patterns associated with changes in health levels that can lead to medical intervention at the early stages of a potential emerging health hazard as part of a risk management plan. We show examples to illustrate how to identify potential risk at work and provide an application of correlation network approaches using simulated mobility data.

Pages: 8 to 13

Copyright: Copyright (c) IARIA, 2017

Publication date: September 10, 2017

Published in: conference

ISSN: 2308-4405

ISBN: 978-1-61208-580-7

Location: Rome, Italy

Dates: from September 10, 2017 to September 14, 2017