Dong Jun Jin
Lasha Zakariashvili
Yang Leng
On the ride to Boston from Waterloo, I felt tired despite sleeping a good number of hours. Thus I came up with the prediction that sleeping positions play a large role in how we feel the next day and the years coming as it puts a strain on the body leading to other medical conditions.
It determines the sleeping position of people who are sleeping in bed by finding out which position is most frequent it can show how the position affects your whole body.
We used the kinect to find joint positions and machine learning to created preset positions for sleeping positions. Whenever someone sleeps in a certain position, we can find the patterns and determine which position they are sleeping in then text to the phone.
The challenges faced were trying to use machine learning for the first time, creating classes with a lot of data, and integrating the whole system together.
The overall challenge of learning new languages and understanding different apis in order to create our project was a huge accomplishment.
We learned how to work as a team and integrate different computer languages together to complete one whole project. We also learned how to work under time constraints.
The next thing for Mobile Sleep Doctor are to be more accurate and have diverse sleeping positions. We hope Mobile Sleep Doctor will be the main tool for people hoping to learn about their sleeping positions.