Inspiration

Learn how to effectively throw a ball.

What it does

The Kine-Fanatic allows us to monitor the accelerations of different critical points on the body in movements like throwing, punching, or shooting a basketball. After analyzing multiple actions, we could classify newly recorded actions based on the data we collected.

How we built it

We accomplished data collection and transmission with BBC Micro:bit programmed in C++. Three sensor micro:bits sent acceleration data to the main hub micro:bit which had a serial link to a computer. We then imported the data into Matlab for analysis and classification.

Challenges we ran into

  • Eliminating gravity from the accelerometer readings.
  • Transmitting data to the central hub from three active micro:bits.
  • Finding the same critical points in different recordings.

Accomplishments that we're proud of

  • Collecting consistent data that was usable for classification.
  • Collecting all data with a single serial link.
  • Classifying new recordings as one of three actions.

What we learned

  • How to filter data based on imperfect sensors.
  • How to utilize low energy Bluetooth connectivity to interconnect our sensors.
  • How to use Matlab classification of data.

What's next for Kine-Fanatic

Using this same method on a much larger sample size would have interesting results. Additionally, attempting to classify a movement as "good" and "bad" could lead us to give the user feedback on their action.

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