Health Data Visualization and Interaction on Smartwatches

The main goal of this project is to design and implement a platform for collecting, visualizing, and exploring COVID-related data on smartwatches. Smartwatches are ubiquities wearable computers that are capable of collecting various types of data, including health data, thanks to a wide range of accurate embedded sensors. Continuous data collection by smartwatches provides us with a reliable platform for further data exploration. To explore the data for a specific purpose, in our case, COVID-19, we need to collect and integrate all related data sources. The integrated data will help us to understand the relationship and correlation between different data sources on the smartwatch. In the second step, novel space-efficient visualization techniques will be designed to visualize the complex integrated data on small displays of smartwatches. Visualization techniques are tools for helping users get insights from the raw data. Adding interaction to data visualizations helps users to get engaged with the data even further. Therefore, in the third step, we will design new bezel interaction techniques helping users to perform various visual data exploration tasks without blocking the display, which is one of the most well-known issues with many of standard interaction techniques on small displays.

Faculty Supervisor:

Pourang Irani

Student:

Ali Neshati

Partner:

MicroVis Technologies Inc

Discipline:

Computer science

Sector:

Health care and social assistance

University:

University of Manitoba