PillChill

PillChill app home page
PillChill app schedule page
PillChill app edit schedule page

Inspiration

When we first heard about the theme of health, there were a lot of different subtopics and possible solutions that came to our mind, but a lot of them already existed and we didn't see anything exciting and special about them. We wanted to target mental health specifically because of how prevalent yet stigmatized it is. We had some experience with machine learning and were really enthusiastic about it, so we came up with the idea of PillChill. We wanted information about medication to be more accessible. To add on, we realized that people with mental health issues as well as other health issues might have a hard time remembering what meds to take each day and when to take them. In addition, people who take anti-depressants and anxiety meds would also have challenges while trying to wean off of them safely and effectively.

What it does

PillChill is an app that uses machine learning software to identify pills from an image that the user takes and directs them to a website that gives the user more information about the pill, so that they can make sure that they know what they are taking. Another feature of PillChill is the schedule page, where the user can input their schedule for their medication. In the future, we want the app to be able to notify the user at a specific time to remind the user to take their medication. It also has a page for alternative remedies, so if the user is struggling with their mental health and needs some additional support along with their prescribed medication, they have access to those resources. The alternative remedies page has a section for ranting, which directs the user to a note page where they can let all their emotions out, which can be very therapeutic.

How we built it

The app was built in Android Studio and we used XML and Java to code it. We used Tensor Flow, which uses Python, for the machine learning aspect of the app for image recognition.

Challenges we ran into

We are not experts at machine learning, or app development, so as we were coding, we ran into problems where certain things weren't working like we thought they should. It took some time to figure out how to tune the machine learning to recognize pills and write code that was better suited for identifying pills. We ran into multiple bugs while coding the app but we kept trying different things, got help from mentors, utilized the Internet and its resources, and persevered through the challenges.

Accomplishments that we're proud of

We are especially proud of the Tensor Flow because machine learning is something that we are very interested in so getting it to work was very exciting. In addition, we are proud of learning how to use calendars in our Android app and figuring out how to make them interactive and clickable.

What we learned

We gained a stronger understanding of machine learning and how to use Tensor Flow. We learned a lot more about app development with Android Studio and all the different widgets and features that we could add to our apps, specifically the calendar feature. We gained a lot more experience with Android Studio and how to make all the pages link together and how to use it effectively to make functional apps.

What's next for PillChill

We want to code the app so that the user will get notification reminders every time they need to take their meds. The notifications would sync up with the schedule that the user inputs. We also want to add a feature that allows users to plan out how they are going to try and wean off of medication, with input from their clinician. This would be integrated with the schedule page of the app.