With Work From Home (WFH) being the new normal, the world is experiencing another pandermic – physical inactivity (PI) and sedentary behavior (SB). Research like A tale of two pandemics: How will COVID-19 and global trends in physical inactivity and sedentary behavior affect one another? has started to analyze the impact of COVID-19 on lifestyle changes, but the collateral effects of COVID situation will not be fully realized for quite some time, especially the adverse health impacts on vulnerable poulations such as obesity and diabetes patients. To help combat this issue, we designed RemindMe, a personalized WFH wellbing assistants. Its purpose is twofold: to help individuals be physically active during lockdown and work-from-home, and (if user consents) collects user data to feed into a longitudinal study exploring the collateral health impacts of COVID.
What RemindMe does
1) Send personalized wellbeing reminders to your desktop, mobile devices, and watch.
Each reminder is generated based on your health portfolio (e.g. age, gender, height, weight). Users can also mark their interest types of wellbeing reminders (e.g. yoga, stretch, pet, meditation), and they can even create their own reminders and share them with the RemindMe community! The algorithms push reminders randomly, but it will take the user's preferences into consideration to make the best personalized reminders.
2) Show your analytics dashboard, which consists of your historic data and how active you're compared to the rest of population in your health condition group.
3) (if user consents) Collect data about their lifestyle habits to support long-term study.
How we built it
Backend: the analytical web application was built with Python's Dash framework and Plotly library for interactive visualizations. The web app was then deployed with Heroku.
Frontend: we used Figma to design the web app, mobile app, logo, and watch app.
Challenges we ran into
Availability of time series data: we struggled to find open, free time-series data that record an individual's activity level and intake. Going forward, we can make use of external APIs like Google Fit APIs to record user's activities, as well as Fitbit and AppleWatch APIs to gather wearable technology data.
What we learned
Figuring out what's feasible in 24-hour, collaborating remotely, iterating on ideas and products
What's next for RemindMe
Once we have enough user data, we can calculate population summary statistics for each age range/gender/physical activity/BMI combination, and show users where they lie on the distribution. As developers, we believe that we shouldn't prescribe users with recommendations. Instead, we should empower users with as much interpretable data as possible to inform their decisions.
Besides, there wasn't enough time for us to build up a functioning front-end web app or the mobile app, and the design is still not comprehensive. The dashboard and the rest of the designed desktop, mobile and iWatch hasn't been connected. For future work, we are hoping to finish building and connect the desktop, mobile and iWatch apps, and gather user data from iWatch. In our ideal final product, once the user signs up and logins via our website, they will be brought to the personalized dashboard app.