I’ve spent the past two weeks focused on developing the tension algorithm while working on prepping for our interim demo & final presentations. After finding the trend about hand span vs wrist movement, I’ve honed in on creating something that uses current hand span to adjust the comparison windows for tension detection. I started this process by using the technique clips to decide on the approximate ratio between hand span & tension time window. I was able to manually adjust the hand span input to produce more accurate results on the technique videos. Next, I’ll be adding in the ability to automatically adjust the algorithm based on handspan & test that according to the test plans outlined in our final presentation.
Although I’ve gotten more promising results with this version of the algorithm, there’s still a high likelihood that the algorithm is inconclusive. In the form we sent out asking the pianist and Dr. Dueck to label tense/ non tense playing, we got conflicting responses accompanied by high confidence ratings. As such, I’m also working on recording and presenting wrist angle data to be sent to the UI as another metric the users can see for their playing. I’ll also provide the output of the tension algorithm in these graphs and provide some more data analysis on the raw angle measurements. This way, we can still provide our users with some feedback while also providing a “beta” tension detecting system.
For the demo and final presentations, I’ve mostly worked on integration and compiling my testing plans and results. I’m still in the process of testing & will finish those by tomorrow to add to our final slides.
In the process of creating our project, I’ve found a new appreciation for open source resources available online. I spent lots of time reading technical blogs on hand landmark models to learn how to effectively use Mediapipe/ Blaze in our project, and got a lot better at distilling these blogs to find what was actually helpful. This skill also came in handy when I was researching piano hand kinematics/ tension—I had to read through a lot of papers and quickly determine what was helpful for our system specifically. Over the course of the project, I’ve grown familiar with most hand landmark models, learned more than I expected about hand physiology, and learned to find information quickly. My main takeaway from this project is that what I can make isn’t really limited by the knowledge I already have, but how quickly I can find and distill the knowledge I can find online.