Fred Hohman
/ CSE Ph.D. Student at GT

mHealth Visual Discovery Dashboard

Dezhi Fang, Fred Hohman, Peter Polack, Hillol Sarker, Minsuk Kahng, Moushumi Sharmin, Mustafa al’Absi, Duen Horng Chau

The Discovery Dashboard interface showing data from a mobile sensor study. Each row corresponds to one participant's data. A user-defined motif (for participant 6012) is selected, and the system automatically finds similar motifs across all participants and highlights them in yellow. This particular motif is a recurring pattern for participant 6012, often found near smoking lapses (vertical red dotted lines).

Abstract

We present Discovery Dashboard, a visual analytics system for exploring large volumes of time series data from mobile medical field studies. Discovery Dashboard offers interactive exploration tools and a data mining motif discovery algorithm to help researchers formulate hypotheses, discover trends and patterns, and ultimately gain a deeper understanding of their data. Discovery Dashboard emphasizes user freedom and flexibility during the data exploration process and enables researchers to do things previously challenging or impossible to do — in the web-browser and in real time. We demonstrate our system visualizing data from a mobile sensor study conducted at the University of Minnesota that included 52 participants who were trying to quit smoking.

Materials

PDF | Video | Poster | BibTeX

Citation

mHealth Visual Discovery Dashboard
Dezhi Fang, Fred Hohman, Peter Polack, Hillol Sarker, Minsuk Kahng, Moushumi Sharmin, Mustafa al’Absi, Duen Horng Chau
Demo, ACM International Joint Conference on Pervasive and Ubiquitous Computing (UBICOMP). Sept 11-15, 2017. Maui, USA.
PDF | Video | Poster | BibTeX

BibTeX

@inproceedings{fang2017mhealth,
  title={mHealth visual discovery dashboard},
  author={Fang, Dezhi and Hohman, Fred and Polack, Peter and Sarker, Hillol and Kahng, Minsuk and Sharmin, Moushumi and al'Absi, Mustafa and Chau, Duen Horng},
  booktitle={Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers},
  pages={237--240},
  year={2017},
  organization={ACM}
}