Data Representation and Modeling for Unleashing the Potential of Multi-Modal Wearable Sensing Systems

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The recent increase in the variety and usage of wearable sensing systems allows for the continuous monitoring of health and wellness of users. The output of these systems enable individuals to make changes to their personal routines in order to minimize exposures to pollutants and maintain healthy levels of exercise. Furthermore, medical practitioners are using these systems to monitor proper activity levels for rehabilitation purposes and to monitor threatening conditions such as heart arrhythmias. However, there is substantial work to be done to facilitate the processing and interpretation of such information in order to maximize impact. This proposal develops a computational framework that models the complex interactions between physiological and environmental factors contributing to an individual's health. The contributions of this award will facilitate the broad adoption of wearable sensing platforms and innovative analytical tools by individuals and medical practitioners. 

  • Wearable devices
  • Physiological Prediction
  • Topological Data Analysis
  • 1552828
  • 2018
  • CPS-PI Meeting 2018
  • Poster
  • Posters (Sessions 8 & 11)
Submitted by Edgar Lobaton on