Data collection for new throwing experiment

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10 participants, 30 hours over 4 days, 90Gb of data – DONE

Andrew has been holed up in the Biomechanics Lab in the Carnegie School of Sport all week with the team collecting data for a new throwing experiment. We are replicating part of Wilson et al (2016); throwers are throwing tennis balls to hit a target at 5m, 10m and 15m. This time, we are collecting enough data (20 hits per distance) to perform uncontrolled manifold analysis (UCM) on the full body motion capture data, turning our attention from the outcome of the throw to the production of the throw.

We are taking advantage of the fully synchronised, integrated set of data collection methods in the Biomechanics Lab and throwing the kitchen sink at this project. We are recording

  • full body kinematics from 70 markers at 250Hz
  • muscle activity from 16 muscles along the throwing arm and torso using wireless EMG markers
  • postural data from two force plates as people take their step to throw
  • high speed (250Hz) video of the throw
  • high speed (250Hz) video of the impact

Data analysis will happen over the summer with the paper planned for the end of 2017. Stay tuned!

 

Lab Meeting 6/2/17; Liu et al (2012), Self Organised Criticality in Learning

This paper shows learners self-organising their training so as to succeed around 50% of the time, which also happens to show up as an optimal rate of feedback. I’ve seen some evidence of this poking around in my coordinated rhythmic movement data and I’m now looking for it on purpose with Dan

Liu, Y. T., Luo, Z. Y., Mayer-Kress, G., & Newell, K. M. (2012). Self-organized criticality and learning a new coordination task. Human Movement Science, 31(1), 40-54.