In hospitals, patients with severe diseases suffer unprecedented amounts of pain. It has been clinically demonstrated that music helps alleviate such pain. Hospitals hire Music Therapists as a form of pain suppressant for these patients. We have decided to automate and digitalize music therapy so it is readily available to patients and individuals.
What it does
Fire Mixtape MD is a web application that provides patients and individuals with music therapy as to alleviate pain, stress, and depression. It does so but utilizing Spotify API's and Genius API's as to search for promising songs, these songs are passed to a Regex algorithm that filters out the songs that are most likely to help alleviate pain based off combinations of vowels and sounds proven to be effective in various academic papers and research projects.
How we built it
Challenges we ran into
Due to it being our first hackaton, we struggled at first trying to implement Spotify API's as well as Genius API's. In the end we decided to write python scripts to web scrape the contents we requiere from web pages.
Accomplishments that we are proud of
We are proud of completing the web app, with all the functionality present in the 24 hours presented to us!
What we learned
We learned that the most important part of a developing any piece of software is cooperating with your team. Teamwork makes the dream work!
What's next for Fire Mixtape MD
Due to the time constraints we had to compromise for a basic version of our web application. In the future we would like to convert our Regex python algorithm to a Python supervised machine learning algorithm that would utilize the pre-existing songs approved by well-known music therapists as its training set. This Machine learning algorithm will analyze the sound waves of the songs as well as its lyrics. To this machine learning algorithm we would continually feed random Spotify songs from all approved genres as to construct the perfect music therapy playlist for those individuals with severe diseases. Furthermore, we would like to convert this web application to an IOS/Android application.