This week, we focused on maintaining the glove as well as moving toward real-time usage of the glove. Some of the connections on our first iteration of the glove came loose as we made gestures that required more movement, so we went back and secured those connections.
We did some analysis on the fake data that we had generated and the real data we collected from the gloves to gain some clarity as to why our models with the real data outperformed out models with the fake data despite having a smaller dataset. The conclusion is that there is a much stronger correlation between the fingers and IMU data in the real data, which makes sense since we were having a hard time modeling the IMU data when we were attempting to mimic the data.
We also added a “random” and “space” category to the classes that our model can output. The “space” class meant to help us eventually allow users to spell words and have those full words outputted as audio (rather than just the individual letters). The “random” class was added to help suppress the audio output as the user transitions between signs. These additions will allow us to move onto using our glove real-time, which is our next step.
We are on schedule and plan on putting the glove together with our software system to use in real-time this week. We are also going to collect data from people with several hand sizes to use to see how well we can get our glove to generalize.