Many people try fitness apps only to stop using them after a few days or weeks due to a lack of motivation. Oftentimes people find themselves in situations where the workouts given to them are too difficult and they cannot complete them, causing them to give up entirely. On the other end of the spectrum are people who attempt workouts that are too easy and get discouraged when they do not see results.

Our goal was to build something that would form habits that users would continue to do even if they stopped using the app. In addition, we wanted the user to push themselves out of their comfort zone, but not so much that they stop using the app. We knew that there were proven strategies to increase the odds someone completes a task, and we thought “What if we made this available within a fitness app?” That’s exactly what we did with FitFeelsGood. What it does

FitFeelsGood uses a form of implementation intentions which are proven to more than double the chances of success. Helps the user make plans with these implementation intentions as well as set goals. Tracks the users progress through goals and completion of planned activities. Uses sentiment analysis on a one sentence response to the question “How are you feeling?” to gauge how user feels after every exercise session. Uses this sentiment analysis to personalize experience to the user, suggesting harder or easier workouts. This allows the app to push the user without pushing them too much, and allows for a custom-tailored experience for each user.

React Native using Google Firebase for backend data management. We also use sentiment analysis APIs.

Clone or download the repo and run using expo start (requires yarn and expo-cli to be installed).

Made with ♥ by Rohan Agarwal, Taran Agnihotri, and Harysh Magesh at HealthTech 2021.