Abstract- Predictive Movements of the Hand lead to better hand-eye coordination


Feel free to offer criticism on my abstract, I’ve only written one prior.

This investigation was designed to better understand human prediction relating to hand-eye coordination.  Test subjects were told that a virtual ball would bounce once on the ground before they would try to hit it with their virtual paddle.  Using a virtual reality system and python algorithm, coordinates were determined for the paddle at each frame and used to conclude the velocity of the hand.  During most trials, the majority of the experimental time involved small adjustments of the hand however there was a large spike in velocity less than 100ms after the bounce.  Because the brain takes at least 100ms send a signal to move the hand, it can be interpreted that the brain must use prior experience or other methods to send a signal to adjust the hand to where it predicts the ball to be before the ball bounces. Thus, part of why humans do not look like uncoordinated toddlers is because large movements are done prior to when it becomes absolutely necessary and smaller adjustments are done after better understanding exactly how the object moves.  This could lead to more research in exactly how hand-eye coordination works.


One thought on “Abstract- Predictive Movements of the Hand lead to better hand-eye coordination

  1. Lindsay

    The abstract looks great, you do an excellent job of clarifying each step of your experimentation process! The only feedback I have is that you might want to end the abstract with some sort of statement about your next steps and what the information you are collecting means for a final conclusion. Great job!


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